import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import nltk
#Read the unlabelled Google reviews set
df = pd.read_excel("D:\\11 Project\\Project\\data.xlsx")
df.shape
(2782, 4)
#Explore the data
df.head()
| Rating | Year | Sentiment | Review | |
|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... |
df.info()
<class 'pandas.core.frame.DataFrame'> RangeIndex: 2782 entries, 0 to 2781 Data columns (total 4 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 Rating 2782 non-null int64 1 Year 2782 non-null int64 2 Sentiment 2782 non-null object 3 Review 2782 non-null object dtypes: int64(2), object(2) memory usage: 87.1+ KB
### Checking Missing values in the Data Set and printing the Percentage for Missing Values for Each Columns ###
count = df.isnull().sum().sort_values(ascending=False)
percentage = ((df.isnull().sum()/len(df)*100)).sort_values(ascending=False)
missing_data = pd.concat([count, percentage], axis=1,
keys=['Count','Percentage'])
print('Count and percentage of missing values for the columns:')
missing_data
Count and percentage of missing values for the columns:
| Count | Percentage | |
|---|---|---|
| Rating | 0 | 0.0 |
| Year | 0 | 0.0 |
| Sentiment | 0 | 0.0 |
| Review | 0 | 0.0 |
### Checking for the Distribution of Default ###
import matplotlib.pyplot as plt
%matplotlib inline
print('Percentage for default\n')
print(round(df.Sentiment.value_counts(normalize=True)*100,2))
round(df.Sentiment.value_counts(normalize=True)*100,2).plot(kind='bar')
plt.title('Percentage Distributions by review type')
plt.show()
Percentage for default Positive 58.7 Negative 41.3 Name: Sentiment, dtype: float64
# Apply first level cleaning
import re
import string
#This function converts to lower-case, removes square bracket, removes numbers and punctuation
def text_clean_1(text):
text = text.lower()
text = re.sub('\[.*?\]', '', text)
text = re.sub('[%s]' % re.escape(string.punctuation), '', text)
text = re.sub('\w*\d\w*', '', text)
return text
cleaned1 = lambda x: text_clean_1(x)
# Let's take a look at the updated text
df['cleaned_description'] = pd.DataFrame(df.Review.apply(cleaned1))
df.head(10)
| Rating | Year | Sentiment | Review | cleaned_description | |
|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... |
| 5 | 1 | 2021 | Negative | My money was deducted 10000 then called verifi... | my money was deducted then called verificatio... |
| 6 | 1 | 2021 | Negative | They charge you and won't issue the gift cards... | they charge you and wont issue the gift cards ... |
| 7 | 1 | 2021 | Negative | Poor customer service. Lost 4.5k Money debited... | poor customer service lost money debited but ... |
| 8 | 1 | 2021 | Negative | I am stuck with it since the entire day. And M... | i am stuck with it since the entire day and my... |
| 9 | 1 | 2021 | Negative | The service of this company is pathetic the mo... | the service of this company is pathetic the mo... |
# Apply a second round of cleaning . This will remove any double spacing and quotes in the test
def text_clean_2(text):
text = re.sub('[‘’“”…]', '', text)
text = re.sub('\n', '', text)
return text
cleaned2 = lambda x: text_clean_2(x)
# Let's take a look at the updated text
df['cleaned_description_new'] = pd.DataFrame(df['cleaned_description'].apply(cleaned2))
df.head(10)
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | |
|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... |
| 5 | 1 | 2021 | Negative | My money was deducted 10000 then called verifi... | my money was deducted then called verificatio... | my money was deducted then called verificatio... |
| 6 | 1 | 2021 | Negative | They charge you and won't issue the gift cards... | they charge you and wont issue the gift cards ... | they charge you and wont issue the gift cards ... |
| 7 | 1 | 2021 | Negative | Poor customer service. Lost 4.5k Money debited... | poor customer service lost money debited but ... | poor customer service lost money debited but ... |
| 8 | 1 | 2021 | Negative | I am stuck with it since the entire day. And M... | i am stuck with it since the entire day and my... | i am stuck with it since the entire day and my... |
| 9 | 1 | 2021 | Negative | The service of this company is pathetic the mo... | the service of this company is pathetic the mo... | the service of this company is pathetic the mo... |
from wordcloud import WordCloud, STOPWORDS
str_data = " " data_dump = df['cleaned_description_new'] for record in data_dump: str_data = str_data + " " + record
wordcloud = WordCloud( stopwords=STOPWORDS, background_color='white', width=1200, height=1000 ).generate(str_data)
plt.imshow(wordcloud) plt.axis('off') plt.show()
#Create the tokens in a seperate column in the dataframe
df['words'] = df.cleaned_description_new.str.strip().str.split('[\W_]+')
df.head()
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | |
|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | [case, id, worst, poor, customer, service, the... |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | [please, dont, install, this, app, people, sto... |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... | [dont, waste, your, time, and, money, on, wooh... |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... | [worst, customer, supportthey, wont, pick, cal... |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... | [was, a, happy, customer, till, i, faced, an, ... |
# Cleaning text of stopwords
from nltk.corpus import stopwords
tokenized_docs_no_stopwords = []
for doc in df['words']:
new_term_vector = []
for word in doc:
if not word in stopwords.words('english'):
new_term_vector.append(word)
tokenized_docs_no_stopwords.append(new_term_vector)
print(tokenized_docs_no_stopwords)
[['case', 'id', 'worst', 'poor', 'customer', 'service', 'giving', 'response', 'days', 'register', 'complaint', 'call', 'disconnected', 'call', 'without', 'giving', 'proper', 'answer', 'way', 'reach', 'customer', 'support', 'tried', 'never', 'change', 'review'], ['please', 'dont', 'install', 'app', 'people', 'stole', 'information', 'related', 'buying', 'pattern', 'card', 'details', 'phone', 'pay', 'details', 'toosame', 'happened', 'today', 'try', 'make', 'fool', 'give', 'peculiar', 'notification', 'phonepay', 'pay', 'think', 'install'], ['dont', 'waste', 'time', 'money', 'woohoo', 'payment', 'successful', 'gift', 'cards', 'refund', 'days', 'customer', 'care', 'clue', 'response', 'raised', 'req', 'mar', 'response', 'last', 'days'], ['worst', 'customer', 'supportthey', 'wont', 'pick', 'calls', 'wont', 'respond', 'mails', 'twice', 'amount', 'deducted', 'status', 'showing', 'failed', 'twice', 'amount', 'deducted', 'status', 'showing', 'processing', 'yet', 'received', 'vouchers', 'even', 'received', 'kyc', 'call', 'well'], ['happy', 'customer', 'till', 'faced', 'error', 'guess', 'even', 'dont', 'reply', 'queries', 'mail', 'worst', 'service', 'support', 'request', 'id', 'kuch', 'sharm', 'kro', 'saalo'], ['money', 'deducted', 'called', 'verification', 'call', 'called', 'email', 'support', 'verification', 'complete', 'day', 'call', 'contact', 'support', 'line', 'busy'], ['charge', 'wont', 'issue', 'gift', 'cards', 'careful', 'pathetic', 'customer', 'service', 'keep', 'hold'], ['poor', 'customer', 'service', 'lost', 'money', 'debited', 'gc', 'generatedno', 'one', 'resolved', 'issue', 'merchants', 'side'], ['stuck', 'since', 'entire', 'day', 'coupons', 'yet', 'processed', 'recommend', 'everyone', 'repeat', 'download', 'fraud'], ['service', 'company', 'pathetic', 'money', 'debited', 'account', 'order', 'got', 'cancelled', 'automatically', 'month', 'credited', 'money', 'back', 'methe', 'company', 'literally', 'useless'], ['app', 'doesnt', 'allow', 'adding', 'gift', 'cards', 'pinkeep', 'saying', 'currently', 'supportedmake', 'thing', 'work', 'gift', 'card', 'pin'], ['purchase', 'google', 'play', 'card', 'payment', 'done', 'play', 'card', 'received', 'old', 'customer', 'woohoo', 'please', 'reply', 'call', 'mail', ''], ['buy', 'gift', 'card', 'dont', 'received', 'gift', 'card', 'costumer', 'support', 'nois', 'valid', 'email', 'reply', 'waiting', 'reply', 'costumer', 'service', 'suggest', 'dont', 'use', 'app', 'totally', 'fake'], ['customer', 'support', 'app', 'incorrigible', 'didnt', 'want', 'buy', 'taj', 'gift', 'card', 'never', 'wouldve', 'bought', 'woohoo', 'e', 'gift', 'many', 'days', 'trying', 'redress', 'problem', 'one', 'available'], ['horrible', 'app', 'horrible', 'customer', 'service', 'money', 'deducted', 'transaction', 'january', 'gift', 'card', 'issued', 'response', 'customer', 'service', 'reply', 'mails', 'would', 'response', 'review', 'stating', 'please', 'mail', 'us', 'query', 'call', 'us', 'would'], ['proper', 'support', 'account', 'blocked', 'since', 'proper', 'response', 'team', 'say', 'solved', 'today', 'disconnect', 'call', 'never', 'done', 'ask', 'call', 'every', 'time', 'call', 'picked', 'ask', 'mail'], ['fraud', 'alert', 'app', 'deducts', 'money', 'doesnt', 'provide', 'gift', 'card', 'refund', 'month', 'since', 'contacting', 'reply', 'mails', 'assist', 'call', 'pathetic', 'app', 'lucrative', 'offers', 'forgery', 'editing', 'add', 'reply', 'please', 'even', 'try', 'nice'], ['worst', 'app', 'payments', 'debited', 'gift', 'card', 'received', 'customer', 'service', 'provide', 'support', 'email', 'support', 'id', 'already', 'sent', 'days', 'back', 'still', 'response'], ['response', 'purchasing', 'card', 'response', 'mails', 'calls', 'bad', 'customer', 'support', 'card', 'processing', 'approved', 'refund', 'money', 'already', 'wrote', 'support', 'multiple', 'times', 'ur', 'support', 'executives', 'busy', 'take', 'call'], ['rubbish', 'customer', 'support', 'u', 'cant', 'contact', 'customer', 'care', 'u', 'mail', 'didnt', 'reply', 'u', 'even', 'week'], ['never', 'seen', 'cheating', 'application', 'day', 'amount', 'got', 'deducted', 'rs', 'upi', 'transaction', 'refund', 'initiated', 'friends', 'persons', 'scammers', 'called', 'times', 'within', 'days', 'reply', 'ticket', 'id'], ['valuable', 'customer', 'purchased', 'gift', 'card', 'many', 'times', 'time', 'tried', 'purchased', 'netmeds', 'gift', 'card', 'unsuccessful', 'generate', 'gift', 'card', 'money', 'deducted', 'paytm', 'wallet', 'every', 'time', 'get', 'connect', 'woohoo', 'customer', 'care', 'call', 'disconnected', 'sent', 'mail'], ['whats', 'point', 'making', 'rewards', 'redeem', 'difficultthe', 'link', 'says', 'appso', 'app', 'needs', 'installed', 'looks', 'like', 'deliberate', 'way', 'keep', 'people', 'redeeming', 'rewards', 'cardwhat', 'happens', 'cards', 'redeemed'], ['fraud', 'company', 'totally', 'spam', 'poor', 'customer', 'support', 'terrible', 'experience', 'debited', 'money', 'ready', 'refund', 'neither', 'got', 'egift', 'card', 'fraud', 'would', 'never', 'used', 'considered', 'ratings', 'never', 'use', 'app', 'wish', 'could', 'give', 'negative'], ['need', 'lot', 'improvements', 'easier', 'buy', 'voucher', 'really', 'hard', 'redeem', 'lot', 'issues', 'happens'], ['redeem', 'e', 'gift', 'card', 'easy', 'card', 'try', 'redeem', 'says', 'support', 'balance', 'view', 'card'], ['dont', 'buy', 'anything', 'woohoo', 'trying', 'buy', 'google', 'gift', 'card', 'money', 'deducted', 'bank', 'woohoo', 'account', 'showing', 'order', 'unsuccess', 'answer', 'call', 'mail', 'class', 'service'], ['good', 'features', 'provides', 'worst', 'user', 'friendliness', 'need', 'user', 'manual', 'understand', 'working'], ['worst', 'service', 'resolve', 'issue', 'asked', 'write', 'mail', 'days', 'reply'], ['working', 'typed', 'password', 'times', 'opening'], ['worst', 'customer', 'support', 'dont', 'respond', 'weeks', 'neither', 'attend', 'calls'], ['always', 'get', 'stuck', 'payment', 'failures', 'also', 'never', 'give', 'cashback', 'offers', 'ill', 'never', 'recommend', 'person', 'use', 'app', 'website', 'buy', 'gift', 'cards', 'self', 'gifting', 'purpose'], ['woohoo', 'given', 'cash', 'redeemable', 'purchasing', 'brand', 'gift', 'card', 'customer', 'support', 'service'], ['worst', 'waste', 'appwhile', 'buying', 'big', 'bazaar', 'voucher', 'asking', 'kyc', 'call', 'customer', 'care', 'times', 'kyc', 'required', 'giving', 'loan', 'one', 'crore', 'complicated', 'procedure', 'better', 'buy', 'paytm', 'magic', 'pineasy', 'within', 'min', 'u', 'get', 'voucher', 'details', 'today', 'wasted', 'hours', 'f'], ['unable', 'purchase', 'google', 'play', 'gift', 'card', 'please', 'check', 'problem', 'solve', 'humble', 'request', 'please'], ['otp', 'received', 'try', 'many', 'times'], ['app', 'trustable', 'today', 'purchased', 'gift', 'card', 'worth', 'gift', 'card', 'didnt', 'come', 'gmail', 'please', 'take', 'action', 'wooho', 'today', 'please', 'give', 'money', 'back'], ['purchased', 'card', 'issued', 'card', 'bad', 'experience'], ['please', 'use', 'worst', 'app', 'im', 'waiting', 'refund', 'month', 'contacted', 'customer', 'support', 'helping', 'refund'], ['bad', 'experience', 'using', 'aap', 'cant', 'send', 'google', 'play', 'gift', 'card', 'friend'], ['every', 'time', 'login', 'otp', 'notification', 'show', 'cant', 'receive', 'otp', 'msg', 'worst', 'customer', 'care', 'service'], ['bought', 'gift', 'card', 'still', 'received', 'pls', 'give', 'gift', 'card', 'reported', 'customer', 'care', 'dont', 'reply'], ['waste', 'app', 'shows', 'always', 'blocked', 'account', 'sent', 'message', 'email', 'proper', 'reply', 'dont', 'install', 'app', 'purchased', 'gift', 'card', 'sill', 'didnt', 'receive', 'scam', 'app'], ['totally', 'fraud', 'appits', 'totally', 'unsecure', 'app', 'transaction', 'histotyno', 'proof', 'transaction', 'information', 'provide', 'customer', 'executive', 'also', 'fraud', 'complaint', 'woohoo', 'app', 'cyber', 'cell'], ['cheat', 'us', 'guys', 'paid', 'myntra', 'gift', 'card', 'amount', 'debited', 'also', 'bank', 'account', 'showed', 'transaction', 'failed', 'customer', 'care', 'says', 'amount', 'credited', 'within', 'hours', 'days', 'even', 'contacted', 'e', 'mail', 'didnt', 'reply'], ['happy', 'customer', 'till', 'faced', 'error', 'guess', 'even', 'dont', 'reply', 'queries', 'mail', 'worst', 'service', 'support', 'request', 'id', 'dont', 'understand', 'issues', 'working', 'since', 'days', 'theres', 'option', 'rate', 'disgusting', 'would', 'go', 'well'], ['report', 'app', 'blocked', 'play', 'store', 'worst', 'customer', 'support', 'worst', 'kyc', 'process', 'never', 'ever', 'try', 'else', 'loose', 'money', 'one', 'help'], ['poor', 'app', 'slow', 'nonresponsive', 'customer', 'service', 'gift', 'card', 'generation', 'fails', 'many', 'times', 'customer', 'support', 'take', 'weeks', 'even', 'respond', 'email', 'refund', 'gift', 'card', 'site', 'responds', 'hours', 'also', 'havent', 'faced', 'failure', 'issue', 'unlike', 'woohoo', 'woohoo', 'even', 'cancels', 'gift', 'card', 'added'], ['fake', 'appi', 'paid', 'dont', 'get', 'gift', 'card'], ['worst', 'app', 'money', 'deduced', 'bank', 'account', 'didnt', 'get', 'gift', 'card', 'talked', 'customer', 'service', 'regarding', 'issue', 'didnt', 'resolve', 'problem', 'email', 'customer', 'support', 'send', 'payment', 'screenshot', 'also', 'days', 'didnt', 'get', 'response', 'fraud', 'people'], ['app', 'like', 'magic', 'pin', 'powered', 'wooho', 'give', 'discount', 'gift', 'card'], ['dont', 'install', 'app', 'poor', 'customer', 'response', 'transaction', 'completed', 'payment', 'deductedno', 'refund', 'initiated', 'yet', 'week', 'go', 'customer', 'care', 'number', 'reachable'], ['used', 'special', 'character', 'password', 'create', 'reply'], ['app', 'every', 'time', 'crush', 'many', 'bug', 'woohoo', 'app', 'app', 'open', 'every', 'time', 'customer', 'care', 'non', 'responsive', 'many', 'problems', 'app'], ['absolutely', 'customer', 'support', 'unfortunately', 'im', 'stuck', 'gift', 'voucher', 'provided', 'company', 'redeemable', 'woohoo', 'ive', 'trying', 'purchase', 'gv', 'last', 'three', 'days', 'website', 'theres', 'error', 'written', 'nonexistent', 'customer', 'care', 'respond', 'automated', 'message'], ['server', 'slow', 'many', 'transaction', 'failed', 'mainly', 'customer', 'service', 'disgusting'], ['app', 'contains', 'star', 'otp', 'coming'], ['refunding', 'money', 'tried', 'contact', 'customer', 'care', 'support', 'several', 'times', 'vain', 'even', 'telling', 'time', 'refund', 'money', 'worst', 'services', 'never', 'buy', 'voucher', 'woohoo', 'edit', 'didnt', 'get', 'money', 'back', 'yet', 'edit', 'response'], ['good', 'need', 'customer', 'support', 'get', 'problem', 'resolution', 'customer', 'support', 'worst', 'application'], ['worst', 'experience', 'many', 'hassle', 'better', 'go', 'flipkart', 'amazon', 'gift', 'cardjust', 'replying', 'reviews', 'resolving', 'issues'], ['stay', 'away', 'fraud', 'company', 'placed', 'order', 'almost', 'week', 'havent', 'received', 'refund', 'yet', 'promised', 'get', 'refund', 'within', 'hrs', 'failed', 'transaction', 'days', 'already', 'call', 'support', 'worthless', 'rece'], ['stupid', 'app', 'many', 'errors', 'website', 'also', 'good', 'works', 'better', 'app', 'redeeming', 'card', 'became', 'nuisance'], ['superb', 'app', 'gift', 'cards', 'given', 'one', 'ordered', 'rs', 'redeem', 'code', 'didnt', 'receive', 'gift', 'card', 'payment', 'also', 'done', 'pleasezz', 'something'], ['placed', 'order', 'amazon', 'gc', 'placed', 'successfully', 'gc', 'issued', 'yet', 'received', 'order', 'confirmation', 'email', 'sms', 'immediately', 'order', 'placement', 'day', 'passed', 'tried', 'reach', 'cc', 'chat', 'phone', 'working', 'worst', 'customer', 'service', 'finally'], ['money', 'debited', 'bank', 'account', 'showing', 'successful', 'gift', 'card', 'failed', 'money', 'didnt', 'refund', 'wrote', 'times', 'mail', 'response', 'please', 'help'], ['buying', 'gift', 'cards', 'experience', 'may', 'easy', 'offers', 'confusing', 'someone', 'buys', 'always', 'prefer', 'gyftr', 'offers', 'construct', 'easy', 'buy', 'every', 'month', 'buy', 'amazon', 'gift', 'voucher', 'gyftr', 'gave', 'constantly', 'discount', 'professional', 'giving', 'nice', 'de'], ['already', 'contacted', 'support', 'team', 'via', 'mail', 'call', 'still', 'response', 'support', 'team', 'reminder', 'mail', 'sent', 'phone', 'support', 'executive', 'able', 'find', 'transaction', 'details', 'technical', 'issue', 'wooohooo', 'thats', 'awesome'], ['processing', 'long', 'time', 'oder', 'gift', 'card'], ['worst', 'app', 'please', 'report', 'app', 'play', 'store', 'lost', 'money', 'even', 'reply', 'customer', 'care', 'ticket', 'dont', 'transact', 'app', 'cheater', 'ticket', 'id'], ['worst', 'app', 'lost', 'money', 'friend', 'couldnt', 'able', 'redeem', 'gift', 'fraud', 'app', 'worst', 'experience', 'please', 'remove', 'app', 'play', 'store', 'asap', 'guys', 'dont', 'waste', 'ur', 'money', 'please', ''], ['worst', 'app', 'many', 'problems', 'first', 'problem', 'login', 'problem', 'guys', 'dont', 'download', 'thats', 'worst', 'app'], ['got', 'gift', 'card', 'woohoo', 'redeemed', 'via', 'app', 'never', 'able', 'login', 'account', 'didnt', 'remember', 'password', 'tried', 'best', 'reset', 'every', 'time', 'shows', 'message', 'wait', 'try', 'tried', 'contacting', 'customer', 'care', 'want', 'drop'], ['garbage', 'ui', 'features', 'youtube', 'video', 'use', 'card', 'small', 'feature', 'maximize', 'whenever', 'try', 'add', 'corporate', 'card', 'definitely', 'get', 'issue', 'need', 'waste', 'time', 'support', 'application', 'full', 'bugs'], ['purchased', 'gc', 'locked', 'woohoo', 'cc', 'responding', 'edit', 'finally', 'received', 'refund', 'never', 'using', 'app'], ['first', 'experience', 'concern', 'proved', 'last', 'experience', 'fraud', 'concern', 'offer', 'discounts', 'cash', 'back', 'portal', 'system', 'confusing', 'customer', 'never', 'gets', 'offer', 'benefits', 'one', 'excuse', 'applied', 'code'], ['worst', 'ever', 'app', 'use', 'gifting', 'help', 'waste', 'time', 'money', 'gifted', 'make', 'trip', 'voucher', 'due', 'pandemic', 'situation', 'completely', 'rude', 'rigid', 'support'], ['pls', 'dnt', 'buy', 'wohoo', 'purchased', 'reliance', 'trend', 'gift', 'card', 'worth', 'working', 'reply', 'support', 'team', 'week', 'raised', 'pathetic', 'service'], ['terrible', 'experience', 'created', 'log', 'transacted', 'transaction', 'shown', 'failed', 'amount', 'debited', 'accountunable', 'reach', 'customer', 'care', 'shiw', 'account', 'disabled', 'log', 'hrswith', 'new', 'age', 'cheating', 'beware'], ['placed', 'order', 'yesterday', 'still', 'process', 'cancelled', 'refunded', 'poor', 'customer', 'service', 'always', 'busy', 'u', 'cant', 'connect', 'mailed', 'support', 'team', 'till', 'reply', 'woohoo', 'hours', 'need', 'refund', 'back'], ['poor', 'service', 'forced', 'use', 'app', 'since', 'website', 'system', 'complicated', 'let', 'redeem', 'gift', 'cards', 'using', 'woohoo', 'balance', 'definitely', 'would', 'recommend', 'using', 'platform'], ['added', 'cards', 'apphad', 'good', 'total', 'balance', 'suddenly', 'debited', 'big', 'amount', 'quoting', 'expiration', 'didnt', 'even', 'notify', 'app', 'says', 'tell', 'validity', 'frauds'], ['unable', 'contact', 'support', 'team', 'gift', 'cards', 'deactivated', 'bought', 'without', 'reason', 'tried', 'contact', 'team', 'via', 'call', 'email', 'response', 'team', 'last', 'days', 'terrible', 'service'], ['card', 'deactivated', 'purchase', 'even', 'send', 'mail', 'ur', 'support', 'said', 'reply', 'within', 'still', 'reply', 'stuck', 'app', 'still', 'way', 'connect', 'support', 'pathetic', 'experience', 'looks', 'like', 'fraud', 'company', 'also', 'file'], ['tried', 'buy', 'gift', 'card', 'several', 'times', 'however', 'said', 'unable', 'generate', 'one', 'deliver', 'promised', 'refunded', 'back', 'hour'], ['dont', 'install', 'fraud'], ['goodi', 'redeem', 'one', 'thousand', 'buy', 'amazon', 'pay', 'amount', 'debited', 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'points', 'u', 'people', 'resume', 'special', 'scheme'], ['delighted', 'joy', 'long', 'set', 'stores', 'locality', 'easily', 'accept', 'woohoo', 'app', 'shopping', 'payments'], ['excellent', 'easy', 'redeem', 'claim', 'voucher', 'face', 'issues'], ['awesome', 'app', 'retailers', 'r', 'aware', 'would', 'nice', 'advertisements'], ['woohoo', 'ooo', 'good', 'app', 'visited', 'aagaman', 'restaurant', 'jayanagar', 'felt', 'easy', 'convenient', 'use', 'woohoo', 'app', 'thanks', 'team', 'keep', 'going'], ['awesome', 'app', 'got', 'rs', 'voucher', 'utilized', 'shoppers', 'stop', 'really', 'great', 'app', 'appreciate', 'woohoo', 'team'], ['loved', 'installed', 'enjoyed', 'shopping', 'mall', 'woohoo', 'app', 'hope', 'see', 'stores', 'added', 'woohoo', 'soon'], ['awesome', 'awesome', 'got', 'rs', 'worth', 'gift', 'voucher', 'waiting', 'offers'], ['thanks', 'woohoo', 'love', 'thanks', 'rs', 'points', 'ordered', 'myntra', 'received', 'order', 'today'], ['received', 'points', 'verification', 'waiting', 'spend'], ['good', 'worthy', 'app', 'spend', 'money', 'gift', 'cards', 'love'], ['verification', 'working'], ['nice', 'app'], ['awesome', 'thanks', 'voucher'], ['nice', 'good', 'deal'], ['liked'], ['nice', 'didnt', 'get', 'rs', 'please', 'dont', 'lie'], ['love', 'got', 'money'], ['nice', 'app', 'love', 'app', 'get', 'gv'], ['fantastic', 'app', 'spending', 'needsmakes', 'life', 'simple'], ['loved', 'best', 'available', 'option', 'segment'], ['nice', 'app', 'anybody', 'try', 'please'], ['good', 'nice', 'keep'], ['cool', 'app', 'useful'], ['nice', 'app', 'love'], ['nice'], ['cool', 'much', 'useful', 'app', 'well', 'designed', 'love', 'interface'], ['amazing', 'app', 'useful', 'day', 'day', 'shopping', 'online', 'offline', 'helps', 'accumulate', 'loyalty', 'rewards', 'points', 'one', 'place', 'gives', 'option', 'redeem', 'big', 'range', 'shopping', 'outlets', 'brands'], ['awesome', 'app', 'love', 'features', 'use', 'others', 'currencies', 'myntra', 'well', 'others', 'also'], ['woohoo', 'make', 'go', 'woopee', 'woopee', 'get', 'see', 'payback', 'points', 'best', 'dont', 'go', 'multiple', 'apps', 'get', 'currency'], ['woohoo', 'ing', 'convenient', 'shop', 'even', 'dont', 'wallet', 'need', 'woohoo'], ['woohoogreat', 'shopping', 'experience', 'feel', 'great', 'cashless', 'shopping', 'experience', 'woohoo', 'app', 'lifestyle', 'great', 'app', 'thank', 'woohoo'], ['simply', 'superb', 'innovative', 'initiative', 'interesting', 'app', 'see', 'something', 'kind', 'long', 'time', 'wooooooooooooooohoooooooooooooo'], ['woohoo', 'rocks', 'awesome', 'conceptsimple', 'clean', 'efficient'], ['cashless', 'shopping', 'experience', 'much', 'needed', 'app', 'shopping', 'without', 'cash'], ['convenient', 'spend', 'money', 'saved', 'offer', 'cards', 'thanks', 'woohoo'], ['missing', 'phone', 'amazing', 'app', 'waiting', 'ios'], ['awesomeness', 'redefined', 'excellent', 'concept', 'perfect', 'execution'], ['amazing', 'app', 'one', 'type', 'app', 'good', 'features'], ['go', 'cashless', 'amazing', 'app', 'must', 'try'], ['super', 'app', 'life', 'simple', 'woohoo'], ['woohoo', 'convenience', 'best'], ['woohoo'], ['good', 'one'], ['woohooooooooooooo'], ['good', 'gifting', 'app'], ['able', 'delete', 'gift', 'vouchers', 'listed', 'shows', 'error', 'added', 'back', 'woohoo', 'account', 'later', 'list', 'selling', 'want', 'delete', 'gift', 'vouchers', 'listed', 'want', 'use', 'shopping', 'allowing', 'enlist', 'deleting'], ['great', 'offers', 'many', 'offers', 'top', 'brands', 'got', 'confused', 'ones', 'shop', 'great', 'offers', 'made', 'buy', 'multiple', 'brands', 'finally', 'seriously', 'love', 'offer'], ['omg', 'amazing', 'app', 'works', 'well', 'download', 'app', 'looked', 'review', 'contains', 'negative', 'comments', 'positive', 'review', 'top', 'average', 'shout', 'positive', 'comment', 'really', 'impressed', 'use', 'app', 'without', 'difficult', 'hope', 'furt'], ['love', 'awesome', 'westside', 'woohoo', 'make', 'good', 'combination', 'many', 'customers', 'added', 'sure', 'personally', 'addicted', 'westside', 'hence', 'woohoo'], ['loved', 'concept', 'woohoo', 'converts', 'credit', 'card', 'payback', 'points', 'valuable', 'amazon', 'gift', 'cards', 'even', 'earn', 'payback', 'points', 'redeeming', 'last', 'minute', 'life', 'saver', 'want', 'send', 'greetings', 'gift', 'cards', 'near', 'dear', 'ones', 'special', 'days', 'awesome', 'app'], ['love', 'range', 'things', 'range', 'items', 'available', 'also', 'food', 'love', 'specially', 'noodle', 'bar', 'buy', 'many', 'things', 'mobile'], ['amazing', 'nice', 'schemes', 'new', 'schemes', 'something', 'worth', 'waiting', 'really', 'sad', 'sometimes', 'validity', 'expires'], ['used', 'used', 'showing', 'spend', 'codes', 'outlets', 'shopping', 'feel', 'like', 'showing', 'spend', 'code', 'even', 'local', 'dairygrocery', 'shop', 'coz', 'love', 'idea', 'spend', 'codes'], ['awesome', 'thing', 'great', 'offers', 'alreadybut', 'want', 'always', 'keep', 'searching', 'offers', 'promotions', 'love', 'using'], ['nice', 'sar', 'aap', 'usmein', 'kyon', 'hata', 'diya', 'usko', 'rahane', 'dijiye', 'na', 'sar', 'request', 'karte', 'hain', 'sar', 'kyon', 'aisa', 'kar', 'rahe', 'ho', 'sar', 'bhejna', 'good', 'night', 'slackness', 'partner', 'waqt'], ['nice', 'app', 'offers', 'updates', 'directly', 'app', 'need', 'search', 'nice', 'keep', 'giving', 'offers'], ['one', 'stop', 'solution', 'digital', 'gifting', 'thanks', 'woohoo', 'giving', 'group', 'gift', 'feature', 'using', 'extensively', 'pool', 'gift', 'weddings', 'birthdays', 'app', 'flows', 'simple', 'user', 'friendly'], ['cool', 'thingsi', 'love', 'flying', 'machine', 'like', 'things', 'get', 'prices', 'specially', 'app'], ['cool', 'app', 'sold', 'unwanted', 'giftcards', 'got', 'office', 'converted', 'cash', 'hassle', 'free'], ['brilliant', 'great', 'app', 'like', 'shop', 'myntra', 'get', 'points', 'dont', 'necessarily', 'spend', 'myntra', 'use', 'lifestyle', 'place', 'like'], ['beautiful', 'person', 'person', 'comments', 'business', 'beautiful', 'day', 'night', 'comments', 'use', 'time', 'comments', 'use', 'information', 'weeks', 'looking', 'forward', 'would', 'like'], ['finally', 'didnt', 'touch', 'van', 'heusen', 'till', 'prices', 'finally', 'offers', 'van', 'heusen', 'awesome', 'office', 'wears', 'wardrobe'], ['superb', 'use', 'shop', 'without', 'app', 'wait', 'sale', 'season', 'get', 'payback', 'points', 'every', 'time', 'shop', 'way', 'better', 'waiting', 'sale', 'season', 'start', 'shopping', 'happy', 'using'], ['top', 'app', 'many', 'stores', 'money', 'transactions', 'easy', 'keep', 'checking', 'offers', 'woohoo', 'every', 'look', 'forward', 'much'], ['shopping', 'spree', 'gone', 'crazy', 'shopperstop'], ['cash', 'currencyrather', 'converting', 'currencies', 'back', 'currency', 'used'], ['bingo', 'got', 'rs', 'voucher', 'woohoooooo', 'redeemed', 'thanks', 'lot'], ['nice', 'app', 'using', 'shopping', 'frequently', 'havent', 'faced', 'problem', 'till'], ['great', 'app', 'gifting', 'never', 'easier', 'thanks', 'woohoo'], ['cool', 'gifting', 'idea', 'liked', 'simple', 'nonfussy', 'way', 'sending', 'gift', 'near', 'ones', 'using', 'woohoo'], ['nice', 'app', 'nice', 'app', 'never', 'knew', 'flying', 'machine', 'cool', 'stuff', 'discovered', 'woohoo', 'discounts'], ['sorry', 'previous', 'review', 'great', 'company', 'great', 'customer', 'service', 'get', 'refunded', 'money', 'within', 'days'], ['love', 'watching', 'movies', 'love', 'watching', 'back', 'back', 'movies', 'tickets', 'cheap', 'woohoo', 'provides', 'cashback', 'discounts', 'movie', 'lovers', 'prefer', 'use', 'woohoo'], ['awesome', 'need', 'android', 'phone', 'easy', 'use', 'great', 'add', 'sign', 'bonus'], ['woohoo', 'awesome', 'concept', 'sell', 'unused', 'gift', 'card'], ['loved', 'swift', 'response', 'couldnt', 'redeem', 'points', 'call', 'centre', 'helped', 'redeem', 'quickly'], ['reward', 'points', 'really', 'cool', 'able', 'use', 'reward', 'points', 'shopping', 'makes', 'shopping', 'experience', 'even', 'enjoyable', 'fun'], ['nice', 'transparent', 'payment', 'payments', 'nd', 'redemption', 'points', 'clearly', 'shown', 'also', 'tracked', 'nice'], ['great', 'way', 'gift', 'digitally', 'avoid', 'gift', 'shops', 'especially', 'pandemic'], ['best', 'get', 'way', 'purchase', 'gift', 'card', 'woohoo', 'good', 'discount', 'great', 'performance', 'nice', 'app'], ['app', 'ap', 'getting', 'free', 'vouchers', 'try', 'ur'], ['good', 'support', 'system', 'issue', 'solved', 'calling', 'help', 'line', 'numbers', 'make', 'easy'], ['definitely', 'easy', 'way', 'gift', 'really', 'prefer', 'online', 'gifting', 'going', 'store', 'anymore'], ['brother', 'app', 'password', 'taking'], ['good', 'work', 'certainly', 'one', 'best', 'ewallet', 'came', 'across'], ['wow', 'offers', 'really', 'cool', 'explored', 'many', 'offers', 'allen', 'solly', 'offers', 'super', 'cool'], ['enjoyed', 'gifting', 'via', 'woohoo', 'family', 'group', 'gifting', 'concept', 'nice'], ['dont', 'get', 'please', 'dont', 'lie', 'u', 'cannot', 'provide'], ['loved', 'want', 'add', 'shopping', 'places', 'like', 'snapdeal', 'ebay'], ['nice', 'girt', 'cards', 'surviving', 'gift', 'cards', 'sent', 'brother', 'feels', 'amazing'], ['good', 'app', 'brother', 'thanks'], ['nice', 'app', 'dont', 'find', 'jabong', 'gv', 'also', 'include', 'flipkart', 'gv', 'pls'], ['useful', 'u', 'redeem', 'points', 'gift', 'card', 'easy', 'share', 'gain', 'points'], ['rockstars', 'games', 'gta', 'vice', 'city'], ['woohoo', 'earn', 'payback', 'points', 'thanks'], ['point', 'loyaltyi', 'gain', 'many', 'loyalty', 'points', 'specially', 'biryani', 'bowl'], ['awesome', 'app', 'earning', 'money', 'thanks', 'woohoo'], ['rahul', 'pd', 'thanks', 'email', 'address'], ['good', 'good', 'good', 'heartily', 'like'], ['good', 'range', 'shopping', 'outlets', 'good', 'brands', 'offer', 'product'], ['cool', 'app', 'earned', 'lot', 'loyalty', 'point', 'referred', 'thanks'], ['md', 'husen', 'like', 'woohoo'], ['awesome', 'concept', 'wow', 'purchase', 'discounted', 'gift', 'cards'], ['mode', 'payment', 'big', 'relief', 'see', 'multiple', 'payment', 'options', 'guysu', 'gotta', 'love'], ['gave', 'bucks', 'free'], ['birth', 'day', 'card', 'greetings'], ['nice', 'app', 'app', 'good', 'fast', 'gift', 'card', 'forwards', 'thanks', 'woohoo', 'teams'], ['awesome', 'deals', 'deals', 'everything', 'really', 'like', 'deals', 'lot', 'want', 'deals', 'brands'], ['rj', 'wohooo', 'kya', 'app', 'h'], ['gugula', 'odisha', 'gugula', 'khordha', 'pichukuli'], ['dont', 'know', 'dis', 'app', 'im', 'downloading', 'whatsapp'], ['nice', 'app', 'friend', 'got', 'gift', 'nice', 'app'], ['one', 'best', 'app', 'buying', 'gift', 'stuffs', 'easy', 'procedures'], ['super', 'apps'], ['good', 'apps', 'ya', 'better', 'apps'], ['habby', 'app'], ['awesome', 'gifting', 'app', 'add', 'paytm', 'mobikwik', 'transactions'], ['great', 'offers', 'amazon', 'gift', 'cards', 'seamless', 'purchase', 'experience', 'loved'], ['nice', 'good', 'going'], ['gautam', 'free', 'recharge'], ['fun', 'shopping', 'makes', 'one', 'shopping', 'addict', 'really', 'nice', 'app'], ['adorable', 'thanks', 'rewarding', 'usappreciation', 'team', 'woohoo'], ['awesome', 'app', 'got', 'spent', 'myntra'], ['enjoy', 'gifting', 'via', 'woohoo', 'fun'], ['app', 'good', 'awesome', ''], ['great', 'app', 'best', 'best', 'appi', 'love', 'thanks'], ['give', 'google', 'play', 'gift', 'cards'], ['good', 'nice', 'app'], ['awesome', 'app', 'provide', 'paytm', 'egv', 'also'], ['easy', 'trusting', 'instant', 'delivery'], ['nice', 'sach', 'yr', 'love', 'app'], ['best', 'app', 'cool', 'app'], ['thanks', 'woohooo', 'nice', 'offer', 'please', 'restart', 'offer'], ['awesome', 'best', 'best'], ['easy', 'easy', 'use'], ['digital', 'love', 'share', 'nice', 'one'], ['nice', 'lovely', 'app', 'nice', 'work'], ['good', 'love', 'much'], ['love', 'app', 'people', 'install'], ['awesome', 'like', 'discounted', 'gift', 'cards'], ['bkb', 'hi', 'friend'], ['trying', 'goog'], ['wooooooohoooooo', 'good'], ['ty'], ['like'], ['abbas', 'lakdawala'], ['mast', 'app'], ['super', 'app'], ['good', 'nice'], ['nice', 'done'], ['sect', 'xxx', 'com'], ['pinku', 'ok'], ['l', 'like'], ['balu', 'gift'], ['super', 'app'], ['love', 'u'], ['op', 'app'], ['nice', 'application'], ['gud', 'one'], ['tariff', 'yaar'], ['great', 'app', 'like'], ['buddy', 'hddh'], ['love', 'love', 'asma'], ['great', 'app', 'amazing', 'app', 'simply', 'love'], ['love', 'app', 'good', 'app', 'sending', 'gifts'], ['love', 'app', 'good', 'app'], ['nice', 'ap', 'like', 'like', 'apps'], ['thanks', 'lot', 'p', 'vouchers', 'p'], ['like', 'many', 'awesome', 'deals'], ['nice', 'app', 'must', 'use', 'least'], ['good', 'application', 'gifting', 'useful', 'app'], ['bad'], ['great', 'app', 'nice', 'app'], ['love', 'variety', 'product', 'variety', 'wide'], ['good', 'app', 'buying', 'gift', 'card'], ['h'], ['best', 'useful'], ['jhakass', 'soo', 'good', 'app'], ['awesome', 'awesome', 'app'], ['loved', 'nice', 'app', 'ģurgaon'], ['nice', 'thanks', 'nice', 'app'], ['nice', 'app', 'great', 'offers'], ['khan', 'best', 'app', 'ever'], ['nice', 'apps', 'good', 'student'], ['super', ''], ['super', 'app'], ['good', 'app', 'amazing', 'app'], ['super', ''], ['super', 'app', 'good', 'gift', 'app'], ['raju', 'wow', 'woohoo'], ['mast', 'app', 'awesome', 'appppppppplol'], ['good', 'apps', 'thanks'], ['loving', 'u'], ['nice', 'app', 'gifting'], ['appreciate', 'ur', 'efforts'], ['easy', 'best', 'service', ''], ['nice', 'appp'], ['nice', 'app'], ['happy', 'diwali', 'must'], ['nice', 'aaps'], ['loved', 'awesome', 'app'], ['good', 'exactly', 'app'], ['good', 'nice'], ['good', 'smooth', 'performance'], ['useful', 'app'], ['like', 'loving'], ['ok', 'good', 'ap'], ['abbey', 'loved', 'app'], ['wow', 'nice'], ['nice', 'app', 'really'], ['superb', 'nice'], ['beautiful', 'good'], ['nice', 'app', 'quit'], ['app', 'good', 'app'], ['good', 'good'], ['awesome', 'great', 'love'], ['nice', 'woooooooo', ''], ['great', 'appconvenient'], ['good', 'app'], ['mranilkumar', 'excellent', 'app'], ['nice', 'app', 'gd', 'app'], ['best', 'app', 'best', 'app', 'guys'], ['happy', 'birthday', 'happy', 'birthday'], ['nice'], ['wow'], ['use'], ['super'], ['wow'], ['like'], ['good'], ['nice', 'application'], ['superintendent'], ['like'], ['experience'], ['super'], ['awesome'], ['bulla'], ['wow'], ['thanks'], ['wow'], ['kk'], ['yes'], ['super'], ['exhalent'], ['awesome'], ['nice', 'app', ''], ['sk', 'nice'], ['awesome', 'app'], ['nice', ''], ['yas', 'yes'], ['wow', 'superb'], ['nice', 'app'], ['good'], ['nice', 'app'], ['nice', ''], ['loved'], ['superb', ''], ['nice', 'app'], ['great', 'working'], ['nice', 'app'], ['rate', 'superb'], ['good', 'great'], ['rakesh', 'superb'], ['good', 'app'], ['good', 'fast'], ['superb', 'xxx'], ['great', 'application'], ['good', 'delivery'], ['nice', 'one'], ['cool', 'app'], ['excellent', 'application'], ['nice', 'app'], ['good', 'app'], ['nice', 'app'], ['good'], ['best', 'loved'], ['good', 'nice'], ['suman', 'good'], ['best', 'app'], ['cool', 'app'], ['srpt', 'good'], ['work'], ['great', 'aap'], ['awesome', 'app'], ['good'], ['good', 'nice'], ['good', 'like'], ['nice', 'app'], ['nice', 'app'], ['nice'], ['great', 'app'], ['amazing', 'app'], ['ki', 'good'], ['best', 'hello'], ['something', 'good'], ['easy', 'use'], ['amazing', 'app'], ['good', 'best'], ['best', 'loved'], ['nice', 'app'], ['nice'], ['good', 'apps'], ['life', 'like'], ['best', 'app'], ['love'], ['good'], ['nice', 'good'], ['nice', 'app'], ['best', 'app'], ['good', 'nice'], ['funny', 'good'], ['nice', 'one'], ['love'], ['nice', 'app'], ['good', 'app'], ['nice', 'app'], ['hi', 'nice'], ['love'], ['awesome', 'app'], ['great', 'app'], ['nice', 'app'], ['best', 'like'], ['good', 'application'], ['nice', 'app'], ['oho', 'good'], ['adi', 'nice'], ['useful'], ['nice', 'aap'], ['jiji', 'great'], ['hhbb', 'good'], ['amazing', 'application'], ['good', 'app', 'good', 'app'], ['nice', ''], ['nice', ''], ['useful'], ['superb'], ['nice'], ['amazing'], ['nice'], ['nice'], ['nice'], ['nice'], ['nice'], ['good'], ['superb'], ['nice'], ['best'], ['good'], ['nice'], ['good'], ['awesome'], ['good'], ['good'], ['best'], ['nice'], ['best'], ['nice'], ['nice'], ['good'], ['nice'], ['awesome'], ['love'], ['good'], ['nice'], ['nice'], ['sexy'], ['good'], ['good'], ['good'], ['awesome'], ['awesome'], ['awesome'], ['nice'], ['excellent'], ['good'], ['good'], ['awesome'], ['good'], ['impressive'], ['good'], ['best'], ['nice'], ['superb'], ['nice'], ['loved'], ['nice', 'nice'], ['good', 'good'], ['awesome', '']]
df['tokenized_docs_no_stopwords'] = tokenized_docs_no_stopwords
df.head(10)
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | tokenized_docs_no_stopwords | |
|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | [case, id, worst, poor, customer, service, the... | [case, id, worst, poor, customer, service, giv... |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | [please, dont, install, this, app, people, sto... | [please, dont, install, app, people, stole, in... |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... | [dont, waste, your, time, and, money, on, wooh... | [dont, waste, time, money, woohoo, payment, su... |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... | [worst, customer, supportthey, wont, pick, cal... | [worst, customer, supportthey, wont, pick, cal... |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... | [was, a, happy, customer, till, i, faced, an, ... | [happy, customer, till, faced, error, guess, e... |
| 5 | 1 | 2021 | Negative | My money was deducted 10000 then called verifi... | my money was deducted then called verificatio... | my money was deducted then called verificatio... | [my, money, was, deducted, then, called, verif... | [money, deducted, called, verification, call, ... |
| 6 | 1 | 2021 | Negative | They charge you and won't issue the gift cards... | they charge you and wont issue the gift cards ... | they charge you and wont issue the gift cards ... | [they, charge, you, and, wont, issue, the, gif... | [charge, wont, issue, gift, cards, careful, pa... |
| 7 | 1 | 2021 | Negative | Poor customer service. Lost 4.5k Money debited... | poor customer service lost money debited but ... | poor customer service lost money debited but ... | [poor, customer, service, lost, money, debited... | [poor, customer, service, lost, money, debited... |
| 8 | 1 | 2021 | Negative | I am stuck with it since the entire day. And M... | i am stuck with it since the entire day and my... | i am stuck with it since the entire day and my... | [i, am, stuck, with, it, since, the, entire, d... | [stuck, since, entire, day, coupons, yet, proc... |
| 9 | 1 | 2021 | Negative | The service of this company is pathetic the mo... | the service of this company is pathetic the mo... | the service of this company is pathetic the mo... | [the, service, of, this, company, is, pathetic... | [service, company, pathetic, money, debited, a... |
df.info()
<class 'pandas.core.frame.DataFrame'> RangeIndex: 2782 entries, 0 to 2781 Data columns (total 8 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 Rating 2782 non-null int64 1 Year 2782 non-null int64 2 Sentiment 2782 non-null object 3 Review 2782 non-null object 4 cleaned_description 2782 non-null object 5 cleaned_description_new 2782 non-null object 6 words 2782 non-null object 7 tokenized_docs_no_stopwords 2782 non-null object dtypes: int64(2), object(6) memory usage: 174.0+ KB
# Stemming and Lemmatization
from nltk.stem.porter import PorterStemmer
from nltk.stem.wordnet import WordNetLemmatizer
porter = PorterStemmer()
wordnet = WordNetLemmatizer()
preprocessed_docs = []
for doc in df['tokenized_docs_no_stopwords']:
final_doc = []
for word in doc:
final_doc.append(porter.stem(word))
#final_doc.append(wordnet.lemmatize(word))
preprocessed_docs.append(final_doc)
print(preprocessed_docs)
[['case', 'id', 'worst', 'poor', 'custom', 'servic', 'give', 'respons', 'day', 'regist', 'complaint', 'call', 'disconnect', 'call', 'without', 'give', 'proper', 'answer', 'way', 'reach', 'custom', 'support', 'tri', 'never', 'chang', 'review'], ['pleas', 'dont', 'instal', 'app', 'peopl', 'stole', 'inform', 'relat', 'buy', 'pattern', 'card', 'detail', 'phone', 'pay', 'detail', 'toosam', 'happen', 'today', 'tri', 'make', 'fool', 'give', 'peculiar', 'notif', 'phonepay', 'pay', 'think', 'instal'], ['dont', 'wast', 'time', 'money', 'woohoo', 'payment', 'success', 'gift', 'card', 'refund', 'day', 'custom', 'care', 'clue', 'respons', 'rais', 'req', 'mar', 'respons', 'last', 'day'], ['worst', 'custom', 'supportthey', 'wont', 'pick', 'call', 'wont', 'respond', 'mail', 'twice', 'amount', 'deduct', 'statu', 'show', 'fail', 'twice', 'amount', 'deduct', 'statu', 'show', 'process', 'yet', 'receiv', 'voucher', 'even', 'receiv', 'kyc', 'call', 'well'], ['happi', 'custom', 'till', 'face', 'error', 'guess', 'even', 'dont', 'repli', 'queri', 'mail', 'worst', 'servic', 'support', 'request', 'id', 'kuch', 'sharm', 'kro', 'saalo'], ['money', 'deduct', 'call', 'verif', 'call', 'call', 'email', 'support', 'verif', 'complet', 'day', 'call', 'contact', 'support', 'line', 'busi'], ['charg', 'wont', 'issu', 'gift', 'card', 'care', 'pathet', 'custom', 'servic', 'keep', 'hold'], ['poor', 'custom', 'servic', 'lost', 'money', 'debit', 'gc', 'generatedno', 'one', 'resolv', 'issu', 'merchant', 'side'], ['stuck', 'sinc', 'entir', 'day', 'coupon', 'yet', 'process', 'recommend', 'everyon', 'repeat', 'download', 'fraud'], ['servic', 'compani', 'pathet', 'money', 'debit', 'account', 'order', 'got', 'cancel', 'automat', 'month', 'credit', 'money', 'back', 'meth', 'compani', 'liter', 'useless'], ['app', 'doesnt', 'allow', 'ad', 'gift', 'card', 'pinkeep', 'say', 'current', 'supportedmak', 'thing', 'work', 'gift', 'card', 'pin'], ['purchas', 'googl', 'play', 'card', 'payment', 'done', 'play', 'card', 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'execut'], ['amaz', 'app', 'one', 'type', 'app', 'good', 'featur'], ['go', 'cashless', 'amaz', 'app', 'must', 'tri'], ['super', 'app', 'life', 'simpl', 'woohoo'], ['woohoo', 'conveni', 'best'], ['woohoo'], ['good', 'one'], ['woohooooooooooooo'], ['good', 'gift', 'app'], ['abl', 'delet', 'gift', 'voucher', 'list', 'show', 'error', 'ad', 'back', 'woohoo', 'account', 'later', 'list', 'sell', 'want', 'delet', 'gift', 'voucher', 'list', 'want', 'use', 'shop', 'allow', 'enlist', 'delet'], ['great', 'offer', 'mani', 'offer', 'top', 'brand', 'got', 'confus', 'one', 'shop', 'great', 'offer', 'made', 'buy', 'multipl', 'brand', 'final', 'serious', 'love', 'offer'], ['omg', 'amaz', 'app', 'work', 'well', 'download', 'app', 'look', 'review', 'contain', 'neg', 'comment', 'posit', 'review', 'top', 'averag', 'shout', 'posit', 'comment', 'realli', 'impress', 'use', 'app', 'without', 'difficult', 'hope', 'furt'], ['love', 'awesom', 'westsid', 'woohoo', 'make', 'good', 'combin', 'mani', 'custom', 'ad', 'sure', 'person', 'addict', 'westsid', 'henc', 'woohoo'], ['love', 'concept', 'woohoo', 'convert', 'credit', 'card', 'payback', 'point', 'valuabl', 'amazon', 'gift', 'card', 'even', 'earn', 'payback', 'point', 'redeem', 'last', 'minut', 'life', 'saver', 'want', 'send', 'greet', 'gift', 'card', 'near', 'dear', 'one', 'special', 'day', 'awesom', 'app'], ['love', 'rang', 'thing', 'rang', 'item', 'avail', 'also', 'food', 'love', 'special', 'noodl', 'bar', 'buy', 'mani', 'thing', 'mobil'], ['amaz', 'nice', 'scheme', 'new', 'scheme', 'someth', 'worth', 'wait', 'realli', 'sad', 'sometim', 'valid', 'expir'], ['use', 'use', 'show', 'spend', 'code', 'outlet', 'shop', 'feel', 'like', 'show', 'spend', 'code', 'even', 'local', 'dairygroceri', 'shop', 'coz', 'love', 'idea', 'spend', 'code'], ['awesom', 'thing', 'great', 'offer', 'alreadybut', 'want', 'alway', 'keep', 'search', 'offer', 'promot', 'love', 'use'], ['nice', 'sar', 'aap', 'usmein', 'kyon', 'hata', 'diya', 'usko', 'rahan', 'dijiy', 'na', 'sar', 'request', 'kart', 'hain', 'sar', 'kyon', 'aisa', 'kar', 'rahe', 'ho', 'sar', 'bhejna', 'good', 'night', 'slack', 'partner', 'waqt'], ['nice', 'app', 'offer', 'updat', 'directli', 'app', 'need', 'search', 'nice', 'keep', 'give', 'offer'], ['one', 'stop', 'solut', 'digit', 'gift', 'thank', 'woohoo', 'give', 'group', 'gift', 'featur', 'use', 'extens', 'pool', 'gift', 'wed', 'birthday', 'app', 'flow', 'simpl', 'user', 'friendli'], ['cool', 'thingsi', 'love', 'fli', 'machin', 'like', 'thing', 'get', 'price', 'special', 'app'], ['cool', 'app', 'sold', 'unwant', 'giftcard', 'got', 'offic', 'convert', 'cash', 'hassl', 'free'], ['brilliant', 'great', 'app', 'like', 'shop', 'myntra', 'get', 'point', 'dont', 'necessarili', 'spend', 'myntra', 'use', 'lifestyl', 'place', 'like'], ['beauti', 'person', 'person', 'comment', 'busi', 'beauti', 'day', 'night', 'comment', 'use', 'time', 'comment', 'use', 'inform', 'week', 'look', 'forward', 'would', 'like'], ['final', 'didnt', 'touch', 'van', 'heusen', 'till', 'price', 'final', 'offer', 'van', 'heusen', 'awesom', 'offic', 'wear', 'wardrob'], ['superb', 'use', 'shop', 'without', 'app', 'wait', 'sale', 'season', 'get', 'payback', 'point', 'everi', 'time', 'shop', 'way', 'better', 'wait', 'sale', 'season', 'start', 'shop', 'happi', 'use'], ['top', 'app', 'mani', 'store', 'money', 'transact', 'easi', 'keep', 'check', 'offer', 'woohoo', 'everi', 'look', 'forward', 'much'], ['shop', 'spree', 'gone', 'crazi', 'shopperstop'], ['cash', 'currencyrath', 'convert', 'currenc', 'back', 'currenc', 'use'], ['bingo', 'got', 'rs', 'voucher', 'woohoooooo', 'redeem', 'thank', 'lot'], ['nice', 'app', 'use', 'shop', 'frequent', 'havent', 'face', 'problem', 'till'], ['great', 'app', 'gift', 'never', 'easier', 'thank', 'woohoo'], ['cool', 'gift', 'idea', 'like', 'simpl', 'nonfussi', 'way', 'send', 'gift', 'near', 'one', 'use', 'woohoo'], ['nice', 'app', 'nice', 'app', 'never', 'knew', 'fli', 'machin', 'cool', 'stuff', 'discov', 'woohoo', 'discount'], ['sorri', 'previou', 'review', 'great', 'compani', 'great', 'custom', 'servic', 'get', 'refund', 'money', 'within', 'day'], ['love', 'watch', 'movi', 'love', 'watch', 'back', 'back', 'movi', 'ticket', 'cheap', 'woohoo', 'provid', 'cashback', 'discount', 'movi', 'lover', 'prefer', 'use', 'woohoo'], ['awesom', 'need', 'android', 'phone', 'easi', 'use', 'great', 'add', 'sign', 'bonu'], ['woohoo', 'awesom', 'concept', 'sell', 'unus', 'gift', 'card'], ['love', 'swift', 'respons', 'couldnt', 'redeem', 'point', 'call', 'centr', 'help', 'redeem', 'quickli'], ['reward', 'point', 'realli', 'cool', 'abl', 'use', 'reward', 'point', 'shop', 'make', 'shop', 'experi', 'even', 'enjoy', 'fun'], ['nice', 'transpar', 'payment', 'payment', 'nd', 'redempt', 'point', 'clearli', 'shown', 'also', 'track', 'nice'], ['great', 'way', 'gift', 'digit', 'avoid', 'gift', 'shop', 'especi', 'pandem'], ['best', 'get', 'way', 'purchas', 'gift', 'card', 'woohoo', 'good', 'discount', 'great', 'perform', 'nice', 'app'], ['app', 'ap', 'get', 'free', 'voucher', 'tri', 'ur'], ['good', 'support', 'system', 'issu', 'solv', 'call', 'help', 'line', 'number', 'make', 'easi'], ['definit', 'easi', 'way', 'gift', 'realli', 'prefer', 'onlin', 'gift', 'go', 'store', 'anymor'], ['brother', 'app', 'password', 'take'], ['good', 'work', 'certainli', 'one', 'best', 'ewallet', 'came', 'across'], ['wow', 'offer', 'realli', 'cool', 'explor', 'mani', 'offer', 'allen', 'solli', 'offer', 'super', 'cool'], ['enjoy', 'gift', 'via', 'woohoo', 'famili', 'group', 'gift', 'concept', 'nice'], ['dont', 'get', 'pleas', 'dont', 'lie', 'u', 'cannot', 'provid'], ['love', 'want', 'add', 'shop', 'place', 'like', 'snapdeal', 'ebay'], ['nice', 'girt', 'card', 'surviv', 'gift', 'card', 'sent', 'brother', 'feel', 'amaz'], ['good', 'app', 'brother', 'thank'], ['nice', 'app', 'dont', 'find', 'jabong', 'gv', 'also', 'includ', 'flipkart', 'gv', 'pl'], ['use', 'u', 'redeem', 'point', 'gift', 'card', 'easi', 'share', 'gain', 'point'], ['rockstar', 'game', 'gta', 'vice', 'citi'], ['woohoo', 'earn', 'payback', 'point', 'thank'], ['point', 'loyaltyi', 'gain', 'mani', 'loyalti', 'point', 'special', 'biryani', 'bowl'], ['awesom', 'app', 'earn', 'money', 'thank', 'woohoo'], ['rahul', 'pd', 'thank', 'email', 'address'], ['good', 'good', 'good', 'heartili', 'like'], ['good', 'rang', 'shop', 'outlet', 'good', 'brand', 'offer', 'product'], ['cool', 'app', 'earn', 'lot', 'loyalti', 'point', 'refer', 'thank'], ['md', 'husen', 'like', 'woohoo'], ['awesom', 'concept', 'wow', 'purchas', 'discount', 'gift', 'card'], ['mode', 'payment', 'big', 'relief', 'see', 'multipl', 'payment', 'option', 'guysu', 'gotta', 'love'], ['gave', 'buck', 'free'], ['birth', 'day', 'card', 'greet'], ['nice', 'app', 'app', 'good', 'fast', 'gift', 'card', 'forward', 'thank', 'woohoo', 'team'], ['awesom', 'deal', 'deal', 'everyth', 'realli', 'like', 'deal', 'lot', 'want', 'deal', 'brand'], ['rj', 'wohooo', 'kya', 'app', 'h'], ['gugula', 'odisha', 'gugula', 'khordha', 'pichukuli'], ['dont', 'know', 'di', 'app', 'im', 'download', 'whatsapp'], ['nice', 'app', 'friend', 'got', 'gift', 'nice', 'app'], ['one', 'best', 'app', 'buy', 'gift', 'stuff', 'easi', 'procedur'], ['super', 'app'], ['good', 'app', 'ya', 'better', 'app'], ['habbi', 'app'], ['awesom', 'gift', 'app', 'add', 'paytm', 'mobikwik', 'transact'], ['great', 'offer', 'amazon', 'gift', 'card', 'seamless', 'purchas', 'experi', 'love'], ['nice', 'good', 'go'], ['gautam', 'free', 'recharg'], ['fun', 'shop', 'make', 'one', 'shop', 'addict', 'realli', 'nice', 'app'], ['ador', 'thank', 'reward', 'usappreci', 'team', 'woohoo'], ['awesom', 'app', 'got', 'spent', 'myntra'], ['enjoy', 'gift', 'via', 'woohoo', 'fun'], ['app', 'good', 'awesom', ''], ['great', 'app', 'best', 'best', 'appi', 'love', 'thank'], ['give', 'googl', 'play', 'gift', 'card'], ['good', 'nice', 'app'], ['awesom', 'app', 'provid', 'paytm', 'egv', 'also'], ['easi', 'trust', 'instant', 'deliveri'], ['nice', 'sach', 'yr', 'love', 'app'], ['best', 'app', 'cool', 'app'], ['thank', 'woohooo', 'nice', 'offer', 'pleas', 'restart', 'offer'], ['awesom', 'best', 'best'], ['easi', 'easi', 'use'], ['digit', 'love', 'share', 'nice', 'one'], ['nice', 'love', 'app', 'nice', 'work'], ['good', 'love', 'much'], ['love', 'app', 'peopl', 'instal'], ['awesom', 'like', 'discount', 'gift', 'card'], ['bkb', 'hi', 'friend'], ['tri', 'goog'], ['wooooooohoooooo', 'good'], ['ty'], ['like'], ['abba', 'lakdawala'], ['mast', 'app'], ['super', 'app'], ['good', 'nice'], ['nice', 'done'], ['sect', 'xxx', 'com'], ['pinku', 'ok'], ['l', 'like'], ['balu', 'gift'], ['super', 'app'], ['love', 'u'], ['op', 'app'], ['nice', 'applic'], ['gud', 'one'], ['tariff', 'yaar'], ['great', 'app', 'like'], ['buddi', 'hddh'], ['love', 'love', 'asma'], ['great', 'app', 'amaz', 'app', 'simpli', 'love'], ['love', 'app', 'good', 'app', 'send', 'gift'], ['love', 'app', 'good', 'app'], ['nice', 'ap', 'like', 'like', 'app'], ['thank', 'lot', 'p', 'voucher', 'p'], ['like', 'mani', 'awesom', 'deal'], ['nice', 'app', 'must', 'use', 'least'], ['good', 'applic', 'gift', 'use', 'app'], ['bad'], ['great', 'app', 'nice', 'app'], ['love', 'varieti', 'product', 'varieti', 'wide'], ['good', 'app', 'buy', 'gift', 'card'], ['h'], ['best', 'use'], ['jhakass', 'soo', 'good', 'app'], ['awesom', 'awesom', 'app'], ['love', 'nice', 'app', 'ģurgaon'], ['nice', 'thank', 'nice', 'app'], ['nice', 'app', 'great', 'offer'], ['khan', 'best', 'app', 'ever'], ['nice', 'app', 'good', 'student'], ['super', ''], ['super', 'app'], ['good', 'app', 'amaz', 'app'], ['super', ''], ['super', 'app', 'good', 'gift', 'app'], ['raju', 'wow', 'woohoo'], ['mast', 'app', 'awesom', 'appppppppplol'], ['good', 'app', 'thank'], ['love', 'u'], ['nice', 'app', 'gift'], ['appreci', 'ur', 'effort'], ['easi', 'best', 'servic', ''], ['nice', 'appp'], ['nice', 'app'], ['happi', 'diwali', 'must'], ['nice', 'aap'], ['love', 'awesom', 'app'], ['good', 'exactli', 'app'], ['good', 'nice'], ['good', 'smooth', 'perform'], ['use', 'app'], ['like', 'love'], ['ok', 'good', 'ap'], ['abbey', 'love', 'app'], ['wow', 'nice'], ['nice', 'app', 'realli'], ['superb', 'nice'], ['beauti', 'good'], ['nice', 'app', 'quit'], ['app', 'good', 'app'], ['good', 'good'], ['awesom', 'great', 'love'], ['nice', 'woooooooo', ''], ['great', 'appconveni'], ['good', 'app'], ['mranilkumar', 'excel', 'app'], ['nice', 'app', 'gd', 'app'], ['best', 'app', 'best', 'app', 'guy'], ['happi', 'birthday', 'happi', 'birthday'], ['nice'], ['wow'], ['use'], ['super'], ['wow'], ['like'], ['good'], ['nice', 'applic'], ['superintend'], ['like'], ['experi'], ['super'], ['awesom'], ['bulla'], ['wow'], ['thank'], ['wow'], ['kk'], ['ye'], ['super'], ['exhal'], ['awesom'], ['nice', 'app', ''], ['sk', 'nice'], ['awesom', 'app'], ['nice', ''], ['ya', 'ye'], ['wow', 'superb'], ['nice', 'app'], ['good'], ['nice', 'app'], ['nice', ''], ['love'], ['superb', ''], ['nice', 'app'], ['great', 'work'], ['nice', 'app'], ['rate', 'superb'], ['good', 'great'], ['rakesh', 'superb'], ['good', 'app'], ['good', 'fast'], ['superb', 'xxx'], ['great', 'applic'], ['good', 'deliveri'], ['nice', 'one'], ['cool', 'app'], ['excel', 'applic'], ['nice', 'app'], ['good', 'app'], ['nice', 'app'], ['good'], ['best', 'love'], ['good', 'nice'], ['suman', 'good'], ['best', 'app'], ['cool', 'app'], ['srpt', 'good'], ['work'], ['great', 'aap'], ['awesom', 'app'], ['good'], ['good', 'nice'], ['good', 'like'], ['nice', 'app'], ['nice', 'app'], ['nice'], ['great', 'app'], ['amaz', 'app'], ['ki', 'good'], ['best', 'hello'], ['someth', 'good'], ['easi', 'use'], ['amaz', 'app'], ['good', 'best'], ['best', 'love'], ['nice', 'app'], ['nice'], ['good', 'app'], ['life', 'like'], ['best', 'app'], ['love'], ['good'], ['nice', 'good'], ['nice', 'app'], ['best', 'app'], ['good', 'nice'], ['funni', 'good'], ['nice', 'one'], ['love'], ['nice', 'app'], ['good', 'app'], ['nice', 'app'], ['hi', 'nice'], ['love'], ['awesom', 'app'], ['great', 'app'], ['nice', 'app'], ['best', 'like'], ['good', 'applic'], ['nice', 'app'], ['oho', 'good'], ['adi', 'nice'], ['use'], ['nice', 'aap'], ['jiji', 'great'], ['hhbb', 'good'], ['amaz', 'applic'], ['good', 'app', 'good', 'app'], ['nice', ''], ['nice', ''], ['use'], ['superb'], ['nice'], ['amaz'], ['nice'], ['nice'], ['nice'], ['nice'], ['nice'], ['good'], ['superb'], ['nice'], ['best'], ['good'], ['nice'], ['good'], ['awesom'], ['good'], ['good'], ['best'], ['nice'], ['best'], ['nice'], ['nice'], ['good'], ['nice'], ['awesom'], ['love'], ['good'], ['nice'], ['nice'], ['sexi'], ['good'], ['good'], ['good'], ['awesom'], ['awesom'], ['awesom'], ['nice'], ['excel'], ['good'], ['good'], ['awesom'], ['good'], ['impress'], ['good'], ['best'], ['nice'], ['superb'], ['nice'], ['love'], ['nice', 'nice'], ['good', 'good'], ['awesom', '']]
# Stemming and Lemmatization
from nltk.stem.porter import PorterStemmer
from nltk.stem.wordnet import WordNetLemmatizer
porter = PorterStemmer()
wordnet = WordNetLemmatizer()
preprocessed_docs = []
for doc in df['tokenized_docs_no_stopwords']:
final_doc = []
for word in doc:
#final_doc.append(porter.stem(word))
final_doc.append(wordnet.lemmatize(word))
preprocessed_docs.append(final_doc)
print(preprocessed_docs)
[['case', 'id', 'worst', 'poor', 'customer', 'service', 'giving', 'response', 'day', 'register', 'complaint', 'call', 'disconnected', 'call', 'without', 'giving', 'proper', 'answer', 'way', 'reach', 'customer', 'support', 'tried', 'never', 'change', 'review'], ['please', 'dont', 'install', 'app', 'people', 'stole', 'information', 'related', 'buying', 'pattern', 'card', 'detail', 'phone', 'pay', 'detail', 'toosame', 'happened', 'today', 'try', 'make', 'fool', 'give', 'peculiar', 'notification', 'phonepay', 'pay', 'think', 'install'], ['dont', 'waste', 'time', 'money', 'woohoo', 'payment', 'successful', 'gift', 'card', 'refund', 'day', 'customer', 'care', 'clue', 'response', 'raised', 'req', 'mar', 'response', 'last', 'day'], ['worst', 'customer', 'supportthey', 'wont', 'pick', 'call', 'wont', 'respond', 'mail', 'twice', 'amount', 'deducted', 'status', 'showing', 'failed', 'twice', 'amount', 'deducted', 'status', 'showing', 'processing', 'yet', 'received', 'voucher', 'even', 'received', 'kyc', 'call', 'well'], ['happy', 'customer', 'till', 'faced', 'error', 'guess', 'even', 'dont', 'reply', 'query', 'mail', 'worst', 'service', 'support', 'request', 'id', 'kuch', 'sharm', 'kro', 'saalo'], ['money', 'deducted', 'called', 'verification', 'call', 'called', 'email', 'support', 'verification', 'complete', 'day', 'call', 'contact', 'support', 'line', 'busy'], ['charge', 'wont', 'issue', 'gift', 'card', 'careful', 'pathetic', 'customer', 'service', 'keep', 'hold'], ['poor', 'customer', 'service', 'lost', 'money', 'debited', 'gc', 'generatedno', 'one', 'resolved', 'issue', 'merchant', 'side'], ['stuck', 'since', 'entire', 'day', 'coupon', 'yet', 'processed', 'recommend', 'everyone', 'repeat', 'download', 'fraud'], ['service', 'company', 'pathetic', 'money', 'debited', 'account', 'order', 'got', 'cancelled', 'automatically', 'month', 'credited', 'money', 'back', 'methe', 'company', 'literally', 'useless'], ['app', 'doesnt', 'allow', 'adding', 'gift', 'card', 'pinkeep', 'saying', 'currently', 'supportedmake', 'thing', 'work', 'gift', 'card', 'pin'], ['purchase', 'google', 'play', 'card', 'payment', 'done', 'play', 'card', 'received', 'old', 'customer', 'woohoo', 'please', 'reply', 'call', 'mail', ''], ['buy', 'gift', 'card', 'dont', 'received', 'gift', 'card', 'costumer', 'support', 'nois', 'valid', 'email', 'reply', 'waiting', 'reply', 'costumer', 'service', 'suggest', 'dont', 'use', 'app', 'totally', 'fake'], ['customer', 'support', 'app', 'incorrigible', 'didnt', 'want', 'buy', 'taj', 'gift', 'card', 'never', 'wouldve', 'bought', 'woohoo', 'e', 'gift', 'many', 'day', 'trying', 'redress', 'problem', 'one', 'available'], ['horrible', 'app', 'horrible', 'customer', 'service', 'money', 'deducted', 'transaction', 'january', 'gift', 'card', 'issued', 'response', 'customer', 'service', 'reply', 'mail', 'would', 'response', 'review', 'stating', 'please', 'mail', 'u', 'query', 'call', 'u', 'would'], ['proper', 'support', 'account', 'blocked', 'since', 'proper', 'response', 'team', 'say', 'solved', 'today', 'disconnect', 'call', 'never', 'done', 'ask', 'call', 'every', 'time', 'call', 'picked', 'ask', 'mail'], ['fraud', 'alert', 'app', 'deducts', 'money', 'doesnt', 'provide', 'gift', 'card', 'refund', 'month', 'since', 'contacting', 'reply', 'mail', 'assist', 'call', 'pathetic', 'app', 'lucrative', 'offer', 'forgery', 'editing', 'add', 'reply', 'please', 'even', 'try', 'nice'], ['worst', 'app', 'payment', 'debited', 'gift', 'card', 'received', 'customer', 'service', 'provide', 'support', 'email', 'support', 'id', 'already', 'sent', 'day', 'back', 'still', 'response'], ['response', 'purchasing', 'card', 'response', 'mail', 'call', 'bad', 'customer', 'support', 'card', 'processing', 'approved', 'refund', 'money', 'already', 'wrote', 'support', 'multiple', 'time', 'ur', 'support', 'executive', 'busy', 'take', 'call'], ['rubbish', 'customer', 'support', 'u', 'cant', 'contact', 'customer', 'care', 'u', 'mail', 'didnt', 'reply', 'u', 'even', 'week'], ['never', 'seen', 'cheating', 'application', 'day', 'amount', 'got', 'deducted', 'r', 'upi', 'transaction', 'refund', 'initiated', 'friend', 'person', 'scammer', 'called', 'time', 'within', 'day', 'reply', 'ticket', 'id'], ['valuable', 'customer', 'purchased', 'gift', 'card', 'many', 'time', 'time', 'tried', 'purchased', 'netmeds', 'gift', 'card', 'unsuccessful', 'generate', 'gift', 'card', 'money', 'deducted', 'paytm', 'wallet', 'every', 'time', 'get', 'connect', 'woohoo', 'customer', 'care', 'call', 'disconnected', 'sent', 'mail'], ['whats', 'point', 'making', 'reward', 'redeem', 'difficultthe', 'link', 'say', 'appso', 'app', 'need', 'installed', 'look', 'like', 'deliberate', 'way', 'keep', 'people', 'redeeming', 'reward', 'cardwhat', 'happens', 'card', 'redeemed'], ['fraud', 'company', 'totally', 'spam', 'poor', 'customer', 'support', 'terrible', 'experience', 'debited', 'money', 'ready', 'refund', 'neither', 'got', 'egift', 'card', 'fraud', 'would', 'never', 'used', 'considered', 'rating', 'never', 'use', 'app', 'wish', 'could', 'give', 'negative'], ['need', 'lot', 'improvement', 'easier', 'buy', 'voucher', 'really', 'hard', 'redeem', 'lot', 'issue', 'happens'], ['redeem', 'e', 'gift', 'card', 'easy', 'card', 'try', 'redeem', 'say', 'support', 'balance', 'view', 'card'], ['dont', 'buy', 'anything', 'woohoo', 'trying', 'buy', 'google', 'gift', 'card', 'money', 'deducted', 'bank', 'woohoo', 'account', 'showing', 'order', 'unsuccess', 'answer', 'call', 'mail', 'class', 'service'], ['good', 'feature', 'provides', 'worst', 'user', 'friendliness', 'need', 'user', 'manual', 'understand', 'working'], ['worst', 'service', 'resolve', 'issue', 'asked', 'write', 'mail', 'day', 'reply'], ['working', 'typed', 'password', 'time', 'opening'], ['worst', 'customer', 'support', 'dont', 'respond', 'week', 'neither', 'attend', 'call'], ['always', 'get', 'stuck', 'payment', 'failure', 'also', 'never', 'give', 'cashback', 'offer', 'ill', 'never', 'recommend', 'person', 'use', 'app', 'website', 'buy', 'gift', 'card', 'self', 'gifting', 'purpose'], ['woohoo', 'given', 'cash', 'redeemable', 'purchasing', 'brand', 'gift', 'card', 'customer', 'support', 'service'], ['worst', 'waste', 'appwhile', 'buying', 'big', 'bazaar', 'voucher', 'asking', 'kyc', 'call', 'customer', 'care', 'time', 'kyc', 'required', 'giving', 'loan', 'one', 'crore', 'complicated', 'procedure', 'better', 'buy', 'paytm', 'magic', 'pineasy', 'within', 'min', 'u', 'get', 'voucher', 'detail', 'today', 'wasted', 'hour', 'f'], ['unable', 'purchase', 'google', 'play', 'gift', 'card', 'please', 'check', 'problem', 'solve', 'humble', 'request', 'please'], ['otp', 'received', 'try', 'many', 'time'], ['app', 'trustable', 'today', 'purchased', 'gift', 'card', 'worth', 'gift', 'card', 'didnt', 'come', 'gmail', 'please', 'take', 'action', 'wooho', 'today', 'please', 'give', 'money', 'back'], ['purchased', 'card', 'issued', 'card', 'bad', 'experience'], ['please', 'use', 'worst', 'app', 'im', 'waiting', 'refund', 'month', 'contacted', 'customer', 'support', 'helping', 'refund'], ['bad', 'experience', 'using', 'aap', 'cant', 'send', 'google', 'play', 'gift', 'card', 'friend'], ['every', 'time', 'login', 'otp', 'notification', 'show', 'cant', 'receive', 'otp', 'msg', 'worst', 'customer', 'care', 'service'], ['bought', 'gift', 'card', 'still', 'received', 'pls', 'give', 'gift', 'card', 'reported', 'customer', 'care', 'dont', 'reply'], ['waste', 'app', 'show', 'always', 'blocked', 'account', 'sent', 'message', 'email', 'proper', 'reply', 'dont', 'install', 'app', 'purchased', 'gift', 'card', 'sill', 'didnt', 'receive', 'scam', 'app'], ['totally', 'fraud', 'appits', 'totally', 'unsecure', 'app', 'transaction', 'histotyno', 'proof', 'transaction', 'information', 'provide', 'customer', 'executive', 'also', 'fraud', 'complaint', 'woohoo', 'app', 'cyber', 'cell'], ['cheat', 'u', 'guy', 'paid', 'myntra', 'gift', 'card', 'amount', 'debited', 'also', 'bank', 'account', 'showed', 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df['preprocessed_docs'] = preprocessed_docs
df.head(5)
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | tokenized_docs_no_stopwords | preprocessed_docs | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | [case, id, worst, poor, customer, service, the... | [case, id, worst, poor, customer, service, giv... | [case, id, worst, poor, customer, service, giv... |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | [please, dont, install, this, app, people, sto... | [please, dont, install, app, people, stole, in... | [please, dont, install, app, people, stole, in... |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... | [dont, waste, your, time, and, money, on, wooh... | [dont, waste, time, money, woohoo, payment, su... | [dont, waste, time, money, woohoo, payment, su... |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... | [worst, customer, supportthey, wont, pick, cal... | [worst, customer, supportthey, wont, pick, cal... | [worst, customer, supportthey, wont, pick, cal... |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... | [was, a, happy, customer, till, i, faced, an, ... | [happy, customer, till, faced, error, guess, e... | [happy, customer, till, faced, error, guess, e... |
df.to_excel(r'D:\\11 Project\\Project\\Celanedfile.xlsx', index = False)
# drop these rows
#df.shape
#df_new = df.drop([365,390,449,592,627,969,975,994,995,996,999,1026,1047,1092,1123,1187,1188,1191,1242,1253,1299,1359,1360,1361,1369,1374,1376,1377,1379,1380,1855,1914,1916,1919,1920,1922,1924,1925,1944,1952,1956,1970,1981,2008,2013,2039,2070,2077,2123,2132,2189,2266,2274,2279,2597,2598,2602,2608,2609,2611,2635,2656,2685,2687,2689,2693,2694,2695,2697,2702,2705,2708,2710,2714,2715,2721,2727])
#df_new = df_new.reset_index(drop=True)
#df_new.shape
#Read the final word Google reviews set for analysis
df_word = pd.read_excel("D:\\11 Project\\Project\\Cleaned_newwordfile.xlsx")
df_word.head(5)
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | tokenized_docs_no_stopwords | preprocessed_docs | word_final | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | case id worst poor customer service giving res... |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | ['please', 'dont', 'install', 'this', 'app', '... | ['please', 'dont', 'install', 'app', 'people',... | ['please', 'dont', 'install', 'app', 'people',... | please dont install app people stole informati... |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... | ['dont', 'waste', 'your', 'time', 'and', 'mone... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | dont waste time money woohoo payment successfu... |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | worst customer supportthey wont pick call wont... |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... | ['was', 'a', 'happy', 'customer', 'till', 'i',... | ['happy', 'customer', 'till', 'faced', 'error'... | ['happy', 'customer', 'till', 'faced', 'error'... | happy customer till faced error guess even don... |
Checking for the Distribution of Default ### import matplotlib.pyplot as plt %matplotlib inline print('Percentage for default\n') print(round(df_word.Sentiment.value_counts(normalize=True)100,2)) round(df.Sentiment.value_counts(normalize=True)100,2).plot(kind='bar') plt.title('Percentage Distributions by review type') plt.show()
from wordcloud import WordCloud, STOPWORDS
str_data = " " data_dump = df_word['word_final'] for record in data_dump: str_data = str_data + " " + record
wordcloud = WordCloud( stopwords=STOPWORDS, background_color='white', width=2400, height=2000 ).generate(str_data)
plt.imshow(wordcloud) plt.axis('off') plt.show()
from wordcloud import WordCloud, STOPWORDS
#Visualize the world cloud
#Concatenate all the words in data to form a string
all_text = ' '.join(word for word in df_word.word_final)
wordcloud_p2 = WordCloud(width=1000, height=1000, colormap='rainbow',background_color='white', mode='RGBA').generate(all_text)
plt.figure(figsize=(20,10))
plt.imshow(wordcloud_p2, interpolation='bilinear')
plt.axis("off")
plt.margins(x=0, y=0)
plt.show()
<Figure size 1440x720 with 0 Axes>
<matplotlib.image.AxesImage at 0x1ac3cd3b288>
(-0.5, 999.5, 999.5, -0.5)
#Explore the results
df_word.groupby('Sentiment')['Sentiment'].count()
Sentiment Negative 1149 Positive 1633 Name: Sentiment, dtype: int64
# Print multiple statements in same line
from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity = "all"
Train Test Split
#We are spliiting the data to train and test 70 -30 .
#Then creating spearte/individual Tarin set by rating to view the percentage
#from sklearn.model_selection import train_test_split
#train, test = train_test_split(df_word, test_size=0.3, random_state=1)
#t_1 = train[train['Rating']==1].sample(800,replace=True)
#t_2 = train[train['Rating']==2].sample(800,replace=True)
#t_3 = train[train['Rating']==3].sample(800,replace=True)
#t_4 = train[train['Rating']==4].sample(800,replace=True)
#t_5 = train[train['Rating']==5].sample(800,replace=True)
#training_bs = pd.concat([t_1, t_2, t_3, t_4, t_5])
#print (train.shape)
#print (training_bs.shape)
#print (test.shape)
# sanity check
#print (df_word.shape)
# Baseline Accuracy
#Explore the results
#train.groupby('Sentiment')['Sentiment'].count()
#Explore the results
#test.groupby('Sentiment')['Sentiment'].count()
#By exploring both the train and test we can see the data distribution is fine.
# reset index before saving
#train = train.reset_index(drop=True)
#train.to_csv('D:\\11 Project\\Project\\training.csv', header=True, index=False, encoding='UTF8')
#test = test.reset_index(drop=True)
#test.to_csv('D:\\11 Project\\Project\\testing.csv', header=True, index=False, encoding='UTF8')
df_new = df_word
df_new.head(2)
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | tokenized_docs_no_stopwords | preprocessed_docs | word_final | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | case id worst poor customer service giving res... |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | ['please', 'dont', 'install', 'this', 'app', '... | ['please', 'dont', 'install', 'app', 'people',... | ['please', 'dont', 'install', 'app', 'people',... | please dont install app people stole informati... |
In sentiment analysis we classify the polarity of given text at document ,sentence or feature level.It tells us but the opinion of it whether is positive , negative or neutral. If we go more advance like beyond polarity we can go for emotional states like angry , sad and happy.
On the cleaned data , uisng the column cleaned_description_new.
#Read the lexicon file
lex_file = open("D:\\11 Project\\Project\\AFINN-111.csv")
lexicons = {}
records = lex_file.readlines()
for record in records:
#print(record) # line contains newline charecter
#print(record.rstrip('\n').split(",")) - to remove new line charecter
lexicons[record.rstrip('\n').split(",")[0]] = int(record.rstrip('\n').split(",")[1])
print(lexicons)
{'abandon': -2, 'abandoned': -2, 'abandons': -2, 'abducted': -2, 'abduction': -2, 'abductions': -2, 'abhor': -3, 'abhorred': -3, 'abhorrent': -3, 'abhors': -3, 'abilities': 2, 'ability': 2, 'aboard': 1, 'absentee': -1, 'absentees': -1, 'absolve': 2, 'absolved': 2, 'absolves': 2, 'absolving': 2, 'absorbed': 1, 'abuse': -3, 'abused': -3, 'abuses': -3, 'abusive': -3, 'accept': 1, 'accepted': 1, 'accepting': 1, 'accepts': 1, 'accident': -2, 'accidental': -2, 'accidentally': -2, 'accidents': -2, 'accomplish': 2, 'accomplished': 2, 'accomplishes': 2, 'accusation': -2, 'accusations': -2, 'accuse': -2, 'accused': -2, 'accuses': -2, 'accusing': -2, 'ache': -2, 'achievable': 1, 'aching': -2, 'acquit': 2, 'acquits': 2, 'acquitted': 2, 'acquitting': 2, 'acrimonious': -3, 'active': 1, 'adequate': 1, 'admire': 3, 'admired': 3, 'admires': 3, 'admiring': 3, 'admit': -1, 'admits': -1, 'admitted': -1, 'admonish': -2, 'admonished': -2, 'adopt': 1, 'adopts': 1, 'adorable': 3, 'adore': 3, 'adored': 3, 'adores': 3, 'advanced': 1, 'advantage': 2, 'advantages': 2, 'adventure': 2, 'adventures': 2, 'adventurous': 2, 'affected': -1, 'affection': 3, 'affectionate': 3, 'afflicted': -1, 'affronted': -1, 'afraid': -2, 'aggravate': -2, 'aggravated': -2, 'aggravates': -2, 'aggravating': -2, 'aggression': -2, 'aggressions': -2, 'aggressive': -2, 'aghast': -2, 'agog': 2, 'agonise': -3, 'agonised': -3, 'agonises': -3, 'agonising': -3, 'agonize': -3, 'agonized': -3, 'agonizes': -3, 'agonizing': -3, 'agree': 1, 'agreeable': 2, 'agreed': 1, 'agreement': 1, 'agrees': 1, 'alarm': -2, 'alarmed': -2, 'alarmist': -2, 'alarmists': -2, 'alas': -1, 'alert': -1, 'alienation': -2, 'alive': 1, 'allergic': -2, 'allow': 1, 'alone': -2, 'amaze': 2, 'amazed': 2, 'amazes': 2, 'amazing': 4, 'ambitious': 2, 'ambivalent': -1, 'amuse': 3, 'amused': 3, 'amusement': 3, 'amusements': 3, 'anger': -3, 'angers': -3, 'angry': -3, 'anguish': -3, 'anguished': -3, 'animosity': -2, 'annoy': -2, 'annoyance': -2, 'annoyed': -2, 'annoying': -2, 'annoys': -2, 'antagonistic': -2, 'anti': -1, 'anticipation': 1, 'anxiety': -2, 'anxious': -2, 'apathetic': -3, 'apathy': -3, 'apeshit': -3, 'apocalyptic': -2, 'apologise': -1, 'apologised': -1, 'apologises': -1, 'apologising': -1, 'apologize': -1, 'apologized': -1, 'apologizes': -1, 'apologizing': -1, 'apology': -1, 'appalled': -2, 'appalling': -2, 'appease': 2, 'appeased': 2, 'appeases': 2, 'appeasing': 2, 'applaud': 2, 'applauded': 2, 'applauding': 2, 'applauds': 2, 'applause': 2, 'appreciate': 2, 'appreciated': 2, 'appreciates': 2, 'appreciating': 2, 'appreciation': 2, 'apprehensive': -2, 'approval': 2, 'approved': 2, 'approves': 2, 'ardent': 1, 'arrest': -2, 'arrested': -3, 'arrests': -2, 'arrogant': -2, 'ashame': -2, 'ashamed': -2, 'ass': -4, 'assassination': -3, 'assassinations': -3, 'asset': 2, 'assets': 2, 'assfucking': -4, 'asshole': -4, 'astonished': 2, 'astound': 3, 'astounded': 3, 'astounding': 3, 'astoundingly': 3, 'astounds': 3, 'attack': -1, 'attacked': -1, 'attacking': -1, 'attacks': -1, 'attract': 1, 'attracted': 1, 'attracting': 2, 'attraction': 2, 'attractions': 2, 'attracts': 1, 'audacious': 3, 'authority': 1, 'avert': -1, 'averted': -1, 'averts': -1, 'avid': 2, 'avoid': -1, 'avoided': -1, 'avoids': -1, 'await': -1, 'awaited': -1, 'awaits': -1, 'award': 3, 'awarded': 3, 'awards': 3, 'awesome': 4, 'awful': -3, 'awkward': -2, 'axe': -1, 'axed': -1, 'backed': 1, 'backing': 2, 'backs': 1, 'bad': -3, 'badass': -3, 'badly': -3, 'bailout': -2, 'bamboozle': -2, 'bamboozled': -2, 'bamboozles': -2, 'ban': -2, 'banish': -1, 'bankrupt': -3, 'bankster': -3, 'banned': -2, 'bargain': 2, 'barrier': -2, 'bastard': -5, 'bastards': -5, 'battle': -1, 'battles': -1, 'beaten': -2, 'beatific': 3, 'beating': -1, 'beauties': 3, 'beautiful': 3, 'beautifully': 3, 'beautify': 3, 'belittle': -2, 'belittled': -2, 'beloved': 3, 'benefit': 2, 'benefits': 2, 'benefitted': 2, 'benefitting': 2, 'bereave': -2, 'bereaved': -2, 'bereaves': -2, 'bereaving': -2, 'best': 3, 'betray': -3, 'betrayal': -3, 'betrayed': -3, 'betraying': -3, 'betrays': -3, 'better': 2, 'bias': -1, 'biased': -2, 'big': 1, 'bitch': -5, 'bitches': -5, 'bitter': -2, 'bitterly': -2, 'bizarre': -2, 'blah': -2, 'blame': -2, 'blamed': -2, 'blames': -2, 'blaming': -2, 'bless': 2, 'blesses': 2, 'blessing': 3, 'blind': -1, 'bliss': 3, 'blissful': 3, 'blithe': 2, 'block': -1, 'blockbuster': 3, 'blocked': -1, 'blocking': -1, 'blocks': -1, 'bloody': -3, 'blurry': -2, 'boastful': -2, 'bold': 2, 'boldly': 2, 'bomb': -1, 'boost': 1, 'boosted': 1, 'boosting': 1, 'boosts': 1, 'bore': -2, 'bored': -2, 'boring': -3, 'bother': -2, 'bothered': -2, 'bothers': -2, 'bothersome': -2, 'boycott': -2, 'boycotted': -2, 'boycotting': -2, 'boycotts': -2, 'brainwashing': -3, 'brave': 2, 'breakthrough': 3, 'breathtaking': 5, 'bribe': -3, 'bright': 1, 'brightest': 2, 'brightness': 1, 'brilliant': 4, 'brisk': 2, 'broke': -1, 'broken': -1, 'brooding': -2, 'bullied': -2, 'bullshit': -4, 'bully': -2, 'bullying': -2, 'bummer': -2, 'buoyant': 2, 'burden': -2, 'burdened': -2, 'burdening': -2, 'burdens': -2, 'calm': 2, 'calmed': 2, 'calming': 2, 'calms': 2, "can't stand": -3, 'cancel': -1, 'cancelled': -1, 'cancelling': -1, 'cancels': -1, 'cancer': -1, 'capable': 1, 'captivated': 3, 'care': 2, 'carefree': 1, 'careful': 2, 'carefully': 2, 'careless': -2, 'cares': 2, 'cashing in': -2, 'casualty': -2, 'catastrophe': -3, 'catastrophic': -4, 'cautious': -1, 'celebrate': 3, 'celebrated': 3, 'celebrates': 3, 'celebrating': 3, 'censor': -2, 'censored': -2, 'censors': -2, 'certain': 1, 'chagrin': -2, 'chagrined': -2, 'challenge': -1, 'chance': 2, 'chances': 2, 'chaos': -2, 'chaotic': -2, 'charged': -3, 'charges': -2, 'charm': 3, 'charming': 3, 'charmless': -3, 'chastise': -3, 'chastised': -3, 'chastises': -3, 'chastising': -3, 'cheat': -3, 'cheated': -3, 'cheater': -3, 'cheaters': -3, 'cheats': -3, 'cheer': 2, 'cheered': 2, 'cheerful': 2, 'cheering': 2, 'cheerless': -2, 'cheers': 2, 'cheery': 3, 'cherish': 2, 'cherished': 2, 'cherishes': 2, 'cherishing': 2, 'chic': 2, 'childish': -2, 'chilling': -1, 'choke': -2, 'choked': -2, 'chokes': -2, 'choking': -2, 'clarifies': 2, 'clarity': 2, 'clash': -2, 'classy': 3, 'clean': 2, 'cleaner': 2, 'clear': 1, 'cleared': 1, 'clearly': 1, 'clears': 1, 'clever': 2, 'clouded': -1, 'clueless': -2, 'cock': -5, 'cocksucker': -5, 'cocksuckers': -5, 'cocky': -2, 'coerced': -2, 'collapse': -2, 'collapsed': -2, 'collapses': -2, 'collapsing': -2, 'collide': -1, 'collides': -1, 'colliding': -1, 'collision': -2, 'collisions': -2, 'colluding': -3, 'combat': -1, 'combats': -1, 'comedy': 1, 'comfort': 2, 'comfortable': 2, 'comforting': 2, 'comforts': 2, 'commend': 2, 'commended': 2, 'commit': 1, 'commitment': 2, 'commits': 1, 'committed': 1, 'committing': 1, 'compassionate': 2, 'compelled': 1, 'competent': 2, 'competitive': 2, 'complacent': -2, 'complain': -2, 'complained': -2, 'complains': -2, 'comprehensive': 2, 'conciliate': 2, 'conciliated': 2, 'conciliates': 2, 'conciliating': 2, 'condemn': -2, 'condemnation': -2, 'condemned': -2, 'condemns': -2, 'confidence': 2, 'confident': 2, 'conflict': -2, 'conflicting': -2, 'conflictive': -2, 'conflicts': -2, 'confuse': -2, 'confused': -2, 'confusing': -2, 'congrats': 2, 'congratulate': 2, 'congratulation': 2, 'congratulations': 2, 'consent': 2, 'consents': 2, 'consolable': 2, 'conspiracy': -3, 'constrained': -2, 'contagion': -2, 'contagions': -2, 'contagious': -1, 'contempt': -2, 'contemptuous': -2, 'contemptuously': -2, 'contend': -1, 'contender': -1, 'contending': -1, 'contentious': -2, 'contestable': -2, 'controversial': -2, 'controversially': -2, 'convince': 1, 'convinced': 1, 'convinces': 1, 'convivial': 2, 'cool': 1, 'cool stuff': 3, 'cornered': -2, 'corpse': -1, 'costly': -2, 'courage': 2, 'courageous': 2, 'courteous': 2, 'courtesy': 2, 'cover-up': -3, 'coward': -2, 'cowardly': -2, 'coziness': 2, 'cramp': -1, 'crap': -3, 'crash': -2, 'crazier': -2, 'craziest': -2, 'crazy': -2, 'creative': 2, 'crestfallen': -2, 'cried': -2, 'cries': -2, 'crime': -3, 'criminal': -3, 'criminals': -3, 'crisis': -3, 'critic': -2, 'criticism': -2, 'criticize': -2, 'criticized': -2, 'criticizes': -2, 'criticizing': -2, 'critics': -2, 'cruel': -3, 'cruelty': -3, 'crush': -1, 'crushed': -2, 'crushes': -1, 'crushing': -1, 'cry': -1, 'crying': -2, 'cunt': -5, 'curious': 1, 'curse': -1, 'cut': -1, 'cute': 2, 'cuts': -1, 'cutting': -1, 'cynic': -2, 'cynical': -2, 'cynicism': -2, 'damage': -3, 'damages': -3, 'damn': -4, 'damned': -4, 'damnit': -4, 'danger': -2, 'daredevil': 2, 'daring': 2, 'darkest': -2, 'darkness': -1, 'dauntless': 2, 'dead': -3, 'deadlock': -2, 'deafening': -1, 'dear': 2, 'dearly': 3, 'death': -2, 'debonair': 2, 'debt': -2, 'deceit': -3, 'deceitful': -3, 'deceive': -3, 'deceived': -3, 'deceives': -3, 'deceiving': -3, 'deception': -3, 'decisive': 1, 'dedicated': 2, 'defeated': -2, 'defect': -3, 'defects': -3, 'defender': 2, 'defenders': 2, 'defenseless': -2, 'defer': -1, 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3, 'praised': 3, 'praises': 3, 'praising': 3, 'pray': 1, 'praying': 1, 'prays': 1, 'prblm': -2, 'prblms': -2, 'prepared': 1, 'pressure': -1, 'pressured': -2, 'pretend': -1, 'pretending': -1, 'pretends': -1, 'pretty': 1, 'prevent': -1, 'prevented': -1, 'preventing': -1, 'prevents': -1, 'prick': -5, 'prison': -2, 'prisoner': -2, 'prisoners': -2, 'privileged': 2, 'proactive': 2, 'problem': -2, 'problems': -2, 'profiteer': -2, 'progress': 2, 'prominent': 2, 'promise': 1, 'promised': 1, 'promises': 1, 'promote': 1, 'promoted': 1, 'promotes': 1, 'promoting': 1, 'propaganda': -2, 'prosecute': -1, 'prosecuted': -2, 'prosecutes': -1, 'prosecution': -1, 'prospect': 1, 'prospects': 1, 'prosperous': 3, 'protect': 1, 'protected': 1, 'protects': 1, 'protest': -2, 'protesters': -2, 'protesting': -2, 'protests': -2, 'proud': 2, 'proudly': 2, 'provoke': -1, 'provoked': -1, 'provokes': -1, 'provoking': -1, 'pseudoscience': -3, 'punish': -2, 'punished': -2, 'punishes': -2, 'punitive': -2, 'pushy': -1, 'puzzled': -2, 'quaking': -2, 'questionable': -2, 'questioned': -1, 'questioning': -1, 'racism': -3, 'racist': -3, 'racists': -3, 'rage': -2, 'rageful': -2, 'rainy': -1, 'rant': -3, 'ranter': -3, 'ranters': -3, 'rants': -3, 'rape': -4, 'rapist': -4, 'rapture': 2, 'raptured': 2, 'raptures': 2, 'rapturous': 4, 'rash': -2, 'ratified': 2, 'reach': 1, 'reached': 1, 'reaches': 1, 'reaching': 1, 'reassure': 1, 'reassured': 1, 'reassures': 1, 'reassuring': 2, 'rebellion': -2, 'recession': -2, 'reckless': -2, 'recommend': 2, 'recommended': 2, 'recommends': 2, 'redeemed': 2, 'refuse': -2, 'refused': -2, 'refusing': -2, 'regret': -2, 'regretful': -2, 'regrets': -2, 'regretted': -2, 'regretting': -2, 'reject': -1, 'rejected': -1, 'rejecting': -1, 'rejects': -1, 'rejoice': 4, 'rejoiced': 4, 'rejoices': 4, 'rejoicing': 4, 'relaxed': 2, 'relentless': -1, 'reliant': 2, 'relieve': 1, 'relieved': 2, 'relieves': 1, 'relieving': 2, 'relishing': 2, 'remarkable': 2, 'remorse': -2, 'repulse': -1, 'repulsed': -2, 'rescue': 2, 'rescued': 2, 'rescues': 2, 'resentful': -2, 'resign': -1, 'resigned': -1, 'resigning': -1, 'resigns': -1, 'resolute': 2, 'resolve': 2, 'resolved': 2, 'resolves': 2, 'resolving': 2, 'respected': 2, 'responsible': 2, 'responsive': 2, 'restful': 2, 'restless': -2, 'restore': 1, 'restored': 1, 'restores': 1, 'restoring': 1, 'restrict': -2, 'restricted': -2, 'restricting': -2, 'restriction': -2, 'restricts': -2, 'retained': -1, 'retard': -2, 'retarded': -2, 'retreat': -1, 'revenge': -2, 'revengeful': -2, 'revered': 2, 'revive': 2, 'revives': 2, 'reward': 2, 'rewarded': 2, 'rewarding': 2, 'rewards': 2, 'rich': 2, 'ridiculous': -3, 'rig': -1, 'rigged': -1, 'right direction': 3, 'rigorous': 3, 'rigorously': 3, 'riot': -2, 'riots': -2, 'risk': -2, 'risks': -2, 'rob': -2, 'robber': -2, 'robed': -2, 'robing': -2, 'robs': -2, 'robust': 2, 'rofl': 4, 'roflcopter': 4, 'roflmao': 4, 'romance': 2, 'rotfl': 4, 'rotflmfao': 4, 'rotflol': 4, 'ruin': -2, 'ruined': -2, 'ruining': -2, 'ruins': -2, 'sabotage': -2, 'sad': -2, 'sadden': -2, 'saddened': -2, 'sadly': -2, 'safe': 1, 'safely': 1, 'safety': 1, 'salient': 1, 'sappy': -1, 'sarcastic': -2, 'satisfied': 2, 'save': 2, 'saved': 2, 'scam': -2, 'scams': -2, 'scandal': -3, 'scandalous': -3, 'scandals': -3, 'scapegoat': -2, 'scapegoats': -2, 'scare': -2, 'scared': -2, 'scary': -2, 'sceptical': -2, 'scold': -2, 'scoop': 3, 'scorn': -2, 'scornful': -2, 'scream': -2, 'screamed': -2, 'screaming': -2, 'screams': -2, 'screwed': -2, 'screwed up': -3, 'scumbag': -4, 'secure': 2, 'secured': 2, 'secures': 2, 'sedition': -2, 'seditious': -2, 'seduced': -1, 'self-confident': 2, 'self-deluded': -2, 'selfish': -3, 'selfishness': -3, 'sentence': -2, 'sentenced': -2, 'sentences': -2, 'sentencing': -2, 'serene': 2, 'severe': -2, 'sexy': 3, 'shaky': -2, 'shame': -2, 'shamed': -2, 'shameful': -2, 'share': 1, 'shared': 1, 'shares': 1, 'shattered': -2, 'shit': -4, 'shithead': -4, 'shitty': -3, 'shock': -2, 'shocked': -2, 'shocking': -2, 'shocks': -2, 'shoot': -1, 'short-sighted': -2, 'short-sightedness': -2, 'shortage': -2, 'shortages': -2, 'shrew': -4, 'shy': -1, 'sick': -2, 'sigh': -2, 'significance': 1, 'significant': 1, 'silencing': -1, 'silly': -1, 'sincere': 2, 'sincerely': 2, 'sincerest': 2, 'sincerity': 2, 'sinful': -3, 'singleminded': -2, 'skeptic': -2, 'skeptical': -2, 'skepticism': -2, 'skeptics': -2, 'slam': -2, 'slash': -2, 'slashed': -2, 'slashes': -2, 'slashing': -2, 'slavery': -3, 'sleeplessness': -2, 'slick': 2, 'slicker': 2, 'slickest': 2, 'sluggish': -2, 'slut': -5, 'smart': 1, 'smarter': 2, 'smartest': 2, 'smear': -2, 'smile': 2, 'smiled': 2, 'smiles': 2, 'smiling': 2, 'smog': -2, 'sneaky': -1, 'snub': -2, 'snubbed': -2, 'snubbing': -2, 'snubs': -2, 'sobering': 1, 'solemn': -1, 'solid': 2, 'solidarity': 2, 'solution': 1, 'solutions': 1, 'solve': 1, 'solved': 1, 'solves': 1, 'solving': 1, 'somber': -2, 'some kind': 0, 'son-of-a-bitch': -5, 'soothe': 3, 'soothed': 3, 'soothing': 3, 'sophisticated': 2, 'sore': -1, 'sorrow': -2, 'sorrowful': -2, 'sorry': -1, 'spam': -2, 'spammer': -3, 'spammers': -3, 'spamming': -2, 'spark': 1, 'sparkle': 3, 'sparkles': 3, 'sparkling': 3, 'speculative': -2, 'spirit': 1, 'spirited': 2, 'spiritless': -2, 'spiteful': -2, 'splendid': 3, 'sprightly': 2, 'squelched': -1, 'stab': -2, 'stabbed': -2, 'stable': 2, 'stabs': -2, 'stall': -2, 'stalled': -2, 'stalling': -2, 'stamina': 2, 'stampede': -2, 'startled': -2, 'starve': -2, 'starved': -2, 'starves': -2, 'starving': -2, 'steadfast': 2, 'steal': -2, 'steals': -2, 'stereotype': -2, 'stereotyped': -2, 'stifled': -1, 'stimulate': 1, 'stimulated': 1, 'stimulates': 1, 'stimulating': 2, 'stingy': -2, 'stolen': -2, 'stop': -1, 'stopped': -1, 'stopping': -1, 'stops': -1, 'stout': 2, 'straight': 1, 'strange': -1, 'strangely': -1, 'strangled': -2, 'strength': 2, 'strengthen': 2, 'strengthened': 2, 'strengthening': 2, 'strengthens': 2, 'stressed': -2, 'stressor': -2, 'stressors': -2, 'stricken': -2, 'strike': -1, 'strikers': -2, 'strikes': -1, 'strong': 2, 'stronger': 2, 'strongest': 2, 'struck': -1, 'struggle': -2, 'struggled': -2, 'struggles': -2, 'struggling': -2, 'stubborn': -2, 'stuck': -2, 'stunned': -2, 'stunning': 4, 'stupid': -2, 'stupidly': -2, 'suave': 2, 'substantial': 1, 'substantially': 1, 'subversive': -2, 'success': 2, 'successful': 3, 'suck': -3, 'sucks': -3, 'suffer': -2, 'suffering': -2, 'suffers': -2, 'suicidal': -2, 'suicide': -2, 'suing': -2, 'sulking': -2, 'sulky': -2, 'sullen': -2, 'sunshine': 2, 'super': 3, 'superb': 5, 'superior': 2, 'support': 2, 'supported': 2, 'supporter': 1, 'supporters': 1, 'supporting': 1, 'supportive': 2, 'supports': 2, 'survived': 2, 'surviving': 2, 'survivor': 2, 'suspect': -1, 'suspected': -1, 'suspecting': -1, 'suspects': -1, 'suspend': -1, 'suspended': -1, 'suspicious': -2, 'swear': -2, 'swearing': -2, 'swears': -2, 'sweet': 2, 'swift': 2, 'swiftly': 2, 'swindle': -3, 'swindles': -3, 'swindling': -3, 'sympathetic': 2, 'sympathy': 2, 'tard': -2, 'tears': -2, 'tender': 2, 'tense': -2, 'tension': -1, 'terrible': -3, 'terribly': -3, 'terrific': 4, 'terrified': -3, 'terror': -3, 'terrorize': -3, 'terrorized': -3, 'terrorizes': -3, 'thank': 2, 'thankful': 2, 'thanks': 2, 'thorny': -2, 'thoughtful': 2, 'thoughtless': -2, 'threat': -2, 'threaten': -2, 'threatened': -2, 'threatening': -2, 'threatens': -2, 'threats': -2, 'thrilled': 5, 'thwart': -2, 'thwarted': -2, 'thwarting': -2, 'thwarts': -2, 'timid': -2, 'timorous': -2, 'tired': -2, 'tits': -2, 'tolerant': 2, 'toothless': -2, 'top': 2, 'tops': 2, 'torn': -2, 'torture': -4, 'tortured': -4, 'tortures': -4, 'torturing': -4, 'totalitarian': -2, 'totalitarianism': -2, 'tout': -2, 'touted': -2, 'touting': -2, 'touts': -2, 'tragedy': -2, 'tragic': -2, 'tranquil': 2, 'trap': -1, 'trapped': -2, 'trauma': -3, 'traumatic': -3, 'travesty': -2, 'treason': -3, 'treasonous': -3, 'treasure': 2, 'treasures': 2, 'trembling': -2, 'tremulous': -2, 'tricked': -2, 'trickery': -2, 'triumph': 4, 'triumphant': 4, 'trouble': -2, 'troubled': -2, 'troubles': -2, 'TRUE': 2, 'trust': 1, 'trusted': 2, 'tumor': -2, 'twat': -5, 'ugly': -3, 'unacceptable': -2, 'unappreciated': -2, 'unapproved': -2, 'unaware': -2, 'unbelievable': -1, 'unbelieving': -1, 'unbiased': 2, 'uncertain': -1, 'unclear': -1, 'uncomfortable': -2, 'unconcerned': -2, 'unconfirmed': -1, 'unconvinced': -1, 'uncredited': -1, 'undecided': -1, 'underestimate': -1, 'underestimated': -1, 'underestimates': -1, 'underestimating': -1, 'undermine': -2, 'undermined': -2, 'undermines': -2, 'undermining': -2, 'undeserving': -2, 'undesirable': -2, 'uneasy': -2, 'unemployment': -2, 'unequal': -1, 'unequaled': 2, 'unethical': -2, 'unfair': -2, 'unfocused': -2, 'unfulfilled': -2, 'unhappy': -2, 'unhealthy': -2, 'unified': 1, 'unimpressed': -2, 'unintelligent': -2, 'united': 1, 'unjust': -2, 'unlovable': -2, 'unloved': -2, 'unmatched': 1, 'unmotivated': -2, 'unprofessional': -2, 'unresearched': -2, 'unsatisfied': -2, 'unsecured': -2, 'unsettled': -1, 'unsophisticated': -2, 'unstable': -2, 'unstoppable': 2, 'unsupported': -2, 'unsure': -1, 'untarnished': 2, 'unwanted': -2, 'unworthy': -2, 'upset': -2, 'upsets': -2, 'upsetting': -2, 'uptight': -2, 'urgent': -1, 'useful': 2, 'usefulness': 2, 'useless': -2, 'uselessness': -2, 'vague': -2, 'validate': 1, 'validated': 1, 'validates': 1, 'validating': 1, 'verdict': -1, 'verdicts': -1, 'vested': 1, 'vexation': -2, 'vexing': -2, 'vibrant': 3, 'vicious': -2, 'victim': -3, 'victimize': -3, 'victimized': -3, 'victimizes': -3, 'victimizing': -3, 'victims': -3, 'vigilant': 3, 'vile': -3, 'vindicate': 2, 'vindicated': 2, 'vindicates': 2, 'vindicating': 2, 'violate': -2, 'violated': -2, 'violates': -2, 'violating': -2, 'violence': -3, 'violent': -3, 'virtuous': 2, 'virulent': -2, 'vision': 1, 'visionary': 3, 'visioning': 1, 'visions': 1, 'vitality': 3, 'vitamin': 1, 'vitriolic': -3, 'vivacious': 3, 'vociferous': -1, 'vulnerability': -2, 'vulnerable': -2, 'walkout': -2, 'walkouts': -2, 'wanker': -3, 'want': 1, 'war': -2, 'warfare': -2, 'warm': 1, 'warmth': 2, 'warn': -2, 'warned': -2, 'warning': -3, 'warnings': -3, 'warns': -2, 'waste': -1, 'wasted': -2, 'wasting': -2, 'wavering': -1, 'weak': -2, 'weakness': -2, 'wealth': 3, 'wealthy': 2, 'weary': -2, 'weep': -2, 'weeping': -2, 'weird': -2, 'welcome': 2, 'welcomed': 2, 'welcomes': 2, 'whimsical': 1, 'whitewash': -3, 'whore': -4, 'wicked': -2, 'widowed': -1, 'willingness': 2, 'win': 4, 'winner': 4, 'winning': 4, 'wins': 4, 'winwin': 3, 'wish': 1, 'wishes': 1, 'wishing': 1, 'withdrawal': -3, 'woebegone': -2, 'woeful': -3, 'won': 3, 'wonderful': 4, 'woo': 3, 'woohoo': 3, 'wooo': 4, 'woow': 4, 'worn': -1, 'worried': -3, 'worry': -3, 'worrying': -3, 'worse': -3, 'worsen': -3, 'worsened': -3, 'worsening': -3, 'worsens': -3, 'worshiped': 3, 'worst': -3, 'worth': 2, 'worthless': -2, 'worthy': 2, 'wow': 4, 'wowow': 4, 'wowww': 4, 'wrathful': -3, 'wreck': -2, 'wrong': -2, 'wronged': -2, 'wtf': -4, 'yeah': 1, 'yearning': 1, 'yeees': 2, 'yes': 1, 'youthful': 2, 'yucky': -2, 'yummy': 3, 'zealot': -2, 'zealots': -2, 'zealous': 2}
#Get the words to be scored by lexicon
corpus = df_new['word_final'].values
corpus[0:5]
array(['case id worst poor customer service giving response day register complaint call disconnected call without giving proper answer way reach customer support tried never change review',
'please dont install app people stole information related buying pattern card detail phone pay detail toosame happened today try make fool give peculiar notification phonepay pay think install',
'dont waste time money woohoo payment successful gift card refund day customer care clue response raised req mar response last day',
'worst customer supportthey wont pick call wont respond mail twice amount deducted status showing failed twice amount deducted status showing processing yet received voucher even received kyc call well',
'happy customer till faced error guess even dont reply query mail worst service support request id kuch sharm kro saalo'],
dtype=object)
#For each record
#For each word in record
#Get the word score (score is a number if the word is in Lexicon, 0 if not)
#Add all the scores and find the ploarity
strength = []
prediction = []
for record in corpus:
#print("record", record)
score = 0
words = record.replace("'","").lower().split()
for word in words:
#print("word", word)
if word in (lexicons):
score = score + lexicons[word]
#print("score",score)
strength.append(score)
#print('strength',strength)
if (score > 0):
prediction.append('positive')
elif (score <0):
prediction.append('negative')
else:
prediction.append('neutral')
print(strength)
print(prediction)
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'positive', 'positive', 'neutral', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive', 'positive']
df_new['strength_affin'] = strength
df_new['prediction_affin']= prediction
df_new.head()
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | tokenized_docs_no_stopwords | preprocessed_docs | word_final | strength_affin | prediction_affin | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | case id worst poor customer service giving res... | -2 | negative |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | ['please', 'dont', 'install', 'this', 'app', '... | ['please', 'dont', 'install', 'app', 'people',... | ['please', 'dont', 'install', 'app', 'people',... | please dont install app people stole informati... | -3 | negative |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... | ['dont', 'waste', 'your', 'time', 'and', 'mone... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | dont waste time money woohoo payment successfu... | 9 | positive |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | worst customer supportthey wont pick call wont... | -5 | negative |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... | ['was', 'a', 'happy', 'customer', 'till', 'i',... | ['happy', 'customer', 'till', 'faced', 'error'... | ['happy', 'customer', 'till', 'faced', 'error'... | happy customer till faced error guess even don... | 0 | neutral |
pd.crosstab(df_new['Sentiment'], df_new['prediction_affin'])
| prediction_affin | negative | neutral | positive |
|---|---|---|---|
| Sentiment | |||
| Negative | 510 | 231 | 408 |
| Positive | 10 | 108 | 1515 |
pd.crosstab(df_new.Sentiment, df_new.prediction_affin).apply(lambda r: r/len(df), axis=1)
| prediction_affin | negative | neutral | positive |
|---|---|---|---|
| Sentiment | |||
| Negative | 0.183321 | 0.083034 | 0.146657 |
| Positive | 0.003595 | 0.038821 | 0.544572 |
#Read the lexicon file
lex_file = open("D:\\11 Project\\Project\\NRC_file - Positive.csv")
lexicons = {}
records = lex_file.readlines()
for record in records:
#print(record) # line contains newline charecter
#print(record.rstrip('\n').split(",")) - to remove new line charecter
lexicons[record.rstrip('\n').split(",")[0]] = int(record.rstrip('\n').split(",")[1])
print(lexicons)
{'aback': 0, 'abacus': 0, 'abandon': 0, 'abandoned': 0, 'abandonment': 0, 'abate': 0, 'abatement': 0, 'abba': 1, 'abbot': 0, 'abbreviate': 0, 'abbreviation': 0, 'abdomen': 0, 'abdominal': 0, 'abduction': 0, 'aberrant': 0, 'aberration': 0, 'abeyance': 0, 'abhor': 0, 'abhorrent': 0, 'abide': 0, 'ability': 1, 'abject': 0, 'ablation': 0, 'ablaze': 0, 'abnormal': 0, 'aboard': 0, 'abode': 0, 'abolish': 0, 'abolition': 0, 'abominable': 0, 'abomination': 0, 'aboriginal': 0, 'abort': 0, 'abortion': 0, 'abortive': 0, 'abound': 0, 'abovementioned': 1, 'abrasion': 0, 'abroad': 0, 'abrogate': 0, 'abrupt': 0, 'abruptly': 0, 'abscess': 0, 'absence': 0, 'absent': 0, 'absentee': 0, 'absenteeism': 0, 'absinthe': 0, 'absolute': 1, 'absolution': 1, 'absorbed': 1, 'absorbent': 0, 'absorbing': 0, 'absorption': 0, 'abstain': 0, 'abstention': 0, 'abstinence': 0, 'abstract': 0, 'abstraction': 0, 'absurd': 0, 'absurdity': 0, 'abundance': 1, 'abundant': 1, 'abuse': 0, 'abutment': 0, 'aby': 0, 'abysmal': 0, 'abyss': 0, 'academic': 1, 'academy': 1, 'accede': 0, 'accelerate': 0, 'acceleration': 0, 'accent': 0, 'accentuate': 0, 'accept': 0, 'acceptable': 1, 'acceptance': 1, 'access': 0, 'accessible': 1, 'accession': 0, 'accessory': 0, 'accident': 0, 'accidental': 0, 'accidentally': 0, 'accolade': 1, 'accommodate': 0, 'accommodation': 1, 'accompaniment': 1, 'accompany': 0, 'accompanying': 0, 'accomplice': 0, 'accomplish': 1, 'accomplished': 1, 'accomplishment': 1, 'accord': 1, 'accordance': 0, 'accordion': 0, 'account': 0, 'accountability': 1, 'accountable': 1, 'accountant': 0, 'accounting': 0, 'accounts': 0, 'accredited': 1, 'accretion': 0, 'accrue': 0, 'accueil': 1, 'accumulate': 0, 'accumulation': 0, 'accuracy': 0, 'accurate': 1, 'accursed': 0, 'accusation': 0, 'accusative': 0, 'accused': 0, 'accuser': 0, 'accusing': 0, 'accustomed': 0, 'ace': 1, 'acetic': 0, 'ache': 0, 'achieve': 1, 'achievement': 1, 'aching': 0, 'acid': 0, 'acidity': 0, 'acknowledge': 0, 'acknowledged': 0, 'acknowledgment': 1, 'acme': 0, 'acoustic': 0, 'acoustics': 0, 'acquaint': 0, 'acquaintance': 0, 'acquainted': 0, 'acquiescence': 0, 'acquire': 1, 'acquiring': 1, 'acquisition': 0, 'acquisitions': 0, 'acreage': 0, 'acres': 0, 'acrobat': 1, 'act': 0, 'acting': 0, 'action': 1, 'actionable': 0, 'active': 0, 'activity': 0, 'actor': 0, 'actual': 1, 'actuality': 0, 'actuary': 0, 'acuity': 1, 'acumen': 1, 'acupuncture': 0, 'acutely': 0, 'adage': 0, 'adamant': 0, 'adapt': 1, 'adaptable': 1, 'add': 0, 'added': 0, 'addendum': 0, 'adder': 0, 'addiction': 0, 'addition': 0, 'additional': 0, 'additive': 0, 'address': 0, 'addressee': 0, 'addresses': 1, 'adept': 1, 'adequacy': 1, 'adequate': 0, 'adhere': 0, 'adherence': 0, 'adherent': 0, 'adhering': 0, 'adhesion': 0, 'adhesive': 0, 'adieu': 0, 'adipose': 0, 'adjacency': 0, 'adjacent': 0, 'adjective': 0, 'adjoining': 0, 'adjourn': 0, 'adjournment': 0, 'adjudicate': 0, 'adjudication': 0, 'adjunct': 1, 'adjust': 0, 'adjustment': 0, 'adjuvant': 0, 'administer': 0, 'administration': 0, 'administrative': 0, 'admirable': 1, 'admiral': 1, 'admiralty': 0, 'admiration': 1, 'admire': 1, 'admirer': 1, 'admissibility': 0, 'admissible': 1, 'admission': 0, 'admit': 0, 'admittance': 0, 'admitted': 0, 'admitting': 0, 'admixture': 0, 'admonition': 0, 'ado': 0, 'adobe': 0, 'adolescence': 0, 'adolescent': 0, 'adopt': 0, 'adoption': 0, 'adorable': 1, 'adoration': 1, 'adore': 1, 'adorn': 0, 'adornment': 0, 'adrift': 0, 'adult': 0, 'adulterated': 0, 'adultery': 0, 'advance': 1, 'advanced': 1, 'advancement': 1, 'advancing': 0, 'advantage': 1, 'advantageous': 1, 'advent': 1, 'adventure': 1, 'adventurer': 0, 'adventurous': 1, 'adversary': 0, 'adverse': 0, 'adversity': 0, 'advertise': 0, 'advertisement': 0, 'advice': 0, 'advisable': 1, 'advise': 1, 'advised': 0, 'advisement': 0, 'adviser': 1, 'advocacy': 1, 'advocate': 0, 'aegis': 0, 'aeration': 0, 'aerial': 0, 'aerodrome': 0, 'aerodynamics': 0, 'aeronautics': 0, 'aeroplane': 0, 'aesthetic': 1, 'aesthetics': 1, 'aetiology': 0, 'afar': 0, 'affable': 1, 'affair': 0, 'affecting': 0, 'affection': 1, 'affections': 0, 'affiche': 0, 'affidavit': 0, 'affiliated': 1, 'affiliation': 0, 'affinity': 0, 'affirm': 1, 'affirmation': 1, 'affirmative': 1, 'affirmatively': 1, 'affix': 0, 'afflict': 0, 'afflicted': 0, 'affliction': 0, 'affluence': 1, 'affluent': 1, 'afford': 1, 'affront': 0, 'afield': 0, 'afore': 0, 'aforementioned': 0, 'aforesaid': 0, 'afraid': 0, 'afresh': 0, 'aft': 0, 'aftermath': 0, 'afternoon': 0, 'aftertaste': 0, 'afterthought': 0, 'aga': 1, 'agate': 0, 'age': 0, 'aged': 0, 'agency': 0, 'agent': 0, 'agglomeration': 0, 'aggravated': 0, 'aggravating': 0, 'aggravation': 0, 'aggregate': 0, 'aggregation': 0, 'aggression': 0, 'aggressive': 0, 'aggressor': 0, 'aghast': 0, 'agile': 1, 'agility': 1, 'agitated': 0, 'agitation': 0, 'agnostic': 0, 'ago': 0, 'agonizing': 0, 'agony': 0, 'agree': 1, 'agreeable': 1, 'agreed': 1, 'agreeing': 1, 'agreement': 1, 'agricultural': 0, 'agriculture': 1, 'aground': 0, 'agua': 0, 'ahead': 1, 'aid': 1, 'aiding': 1, 'ail': 0, 'ailing': 0, 'ailment': 0, 'aim': 0, 'aimless': 0, 'air': 0, 'airbag': 0, 'airlift': 0, 'airline': 0, 'airman': 0, 'airplane': 0, 'airport': 0, 'airs': 0, 'airship': 0, 'aisle': 0, 'ait': 0, 'ajar': 0, 'akin': 0, 'alabaster': 1, 'alarm': 0, 'alarming': 0, 'alb': 0, 'album': 0, 'alchemy': 0, 'alcohol': 0, 'alcoholism': 0, 'alcove': 0, 'alert': 0, 'alertness': 1, 'alerts': 0, 'alfalfa': 0, 'algebra': 0, 'algebraic': 0, 'algorithm': 0, 'alibi': 0, 'alien': 0, 'alienate': 0, 'alienated': 0, 'alienation': 0, 'alight': 0, 'aligned': 0, 'alignment': 0, 'alike': 0, 'alimentation': 1, 'alimony': 0, 'aliquot': 0, 'alive': 1, 'alkali': 0, 'alkaloids': 0, 'allay': 1, 'allegation': 0, 'allege': 0, 'alleged': 0, 'allegiance': 1, 'allegorical': 0, 'allegory': 0, 'allegro': 1, 'alleviate': 1, 'alleviation': 1, 'alley': 0, 'alliance': 0, 'allied': 1, 'alligator': 0, 'allocate': 0, 'allocation': 0, 'allot': 0, 'allotment': 0, 'allowable': 1, 'allowance': 0, 'allowed': 0, 'alloy': 0, 'allure': 1, 'alluring': 1, 'allusion': 0, 'alluvial': 0, 'ally': 1, 'almanac': 0, 'almighty': 1, 'aloft': 0, 'aloha': 1, 'alongside': 0, 'aloof': 0, 'aloud': 0, 'alphabet': 0, 'alphabetical': 0, 'altar': 0, 'alter': 0, 'alteration': 0, 'altercation': 0, 'altered': 0, 'alternate': 0, 'alternative': 0, 'altitude': 0, 'alto': 0, 'altogether': 0, 'alumnus': 0, 'alveolar': 0, 'amalgam': 0, 'amalgamation': 0, 'amass': 0, 'amateur': 0, 'amaze': 0, 'amazement': 0, 'amazingly': 1, 'ambassador': 1, 'amber': 0, 'ambient': 0, 'ambiguity': 0, 'ambiguous': 0, 'ambit': 0, 'ambition': 1, 'ambitious': 0, 'ambulance': 0, 'ambush': 0, 'ameliorate': 1, 'amen': 1, 'amenable': 1, 'amend': 1, 'amendment': 0, 'amends': 1, 'amenity': 1, 'amethyst': 0, 'amiable': 1, 'amicable': 1, 'amid': 0, 'amidst': 0, 'ammonia': 0, 'ammunition': 0, 'amnesia': 0, 'amnesty': 1, 'amorphous': 0, 'amortization': 0, 'amount': 0, 'amour': 1, 'ampersand': 0, 'amphetamines': 0, 'amphibian': 0, 'amphibious': 0, 'amphitheater': 0, 'amplification': 0, 'amplify': 0, 'amplitude': 0, 'amply': 0, 'amputation': 0, 'amulet': 0, 'amuse': 1, 'amused': 1, 'amusement': 1, 'amusing': 1, 'ana': 0, 'anaconda': 0, 'anaesthesia': 0, 'anaesthetic': 0, 'anal': 0, 'analgesic': 0, 'analogous': 0, 'analogue': 0, 'analogy': 0, 'analysis': 0, 'analyst': 1, 'analytic': 0, 'analyze': 0, 'analyzer': 0, 'anarchism': 0, 'anarchist': 0, 'anarchy': 0, 'anastomosis': 0, 'anathema': 0, 'anatomic': 0, 'anatomy': 0, 'ancestor': 0, 'ancestral': 0, 'ancestry': 0, 'anchor': 1, 'anchorage': 1, 'ancient': 0, 'ancillary': 0, 'androgen': 0, 'anemone': 0, 'anew': 0, 'angel': 1, 'angelic': 1, 'anger': 0, 'angina': 0, 'angiography': 0, 'angle': 0, 'angling': 0, 'angry': 0, 'anguish': 0, 'angular': 0, 'anhydrous': 0, 'animal': 0, 'animate': 1, 'animated': 1, 'animation': 0, 'animosity': 0, 'animus': 0, 'ankle': 0, 'annals': 0, 'annex': 0, 'annexation': 0, 'annexe': 0, 'annihilate': 0, 'annihilated': 0, 'annihilation': 0, 'annotate': 0, 'annotation': 0, 'announce': 0, 'announcement': 0, 'annoy': 0, 'annoyance': 0, 'annoying': 0, 'annuity': 0, 'annul': 0, 'annular': 0, 'annulment': 0, 'annulus': 0, 'anointing': 0, 'anomalous': 0, 'anomaly': 0, 'anon': 0, 'anonymous': 0, 'answer': 0, 'answerable': 0, 'answering': 0, 'ant': 0, 'antagonism': 0, 'antagonist': 0, 'antagonistic': 0, 'ante': 0, 'antecedent': 0, 'antelope': 0, 'antenna': 0, 'anterior': 0, 'anthem': 0, 'anthology': 0, 'anthrax': 0, 'anthropology': 0, 'antibiotic': 0, 'antibiotics': 1, 'antichrist': 0, 'anticipation': 0, 'anticipatory': 0, 'antidote': 1, 'antifungal': 1, 'antimony': 0, 'antipathy': 0, 'antiquarian': 0, 'antiquated': 0, 'antique': 1, 'antiquity': 0, 'antiseptic': 1, 'antisocial': 0, 'antithesis': 0, 'antithetical': 0, 'antiviral': 0, 'antler': 0, 'anvil': 0, 'anxiety': 0, 'anxious': 0, 'aorta': 0, 'apace': 0, 'apache': 0, 'apartment': 0, 'apathetic': 0, 'apathy': 0, 'ape': 0, 'aperture': 0, 'apex': 0, 'aphid': 0, 'apiece': 0, 'aplomb': 1, 'apocalyptic': 0, 'apologetic': 1, 'apologist': 0, 'apologize': 1, 'apology': 1, 'apostasy': 0, 'apostate': 0, 'apostle': 1, 'apostolic': 0, 'apostrophe': 0, 'appalling': 0, 'apparatus': 0, 'apparel': 0, 'apparently': 0, 'apparition': 0, 'appeal': 0, 'appearance': 0, 'appease': 0, 'appellant': 0, 'append': 0, 'appendage': 0, 'appendicitis': 0, 'appendix': 0, 'appetite': 0, 'appetizer': 0, 'applause': 1, 'apple': 0, 'appliance': 0, 'appliances': 0, 'applicability': 0, 'applicable': 0, 'applicant': 0, 'application': 0, 'apply': 0, 'appoint': 0, 'appointment': 0, 'appointments': 0, 'apportion': 0, 'apportionment': 0, 'appraise': 0, 'appreciable': 0, 'appreciation': 1, 'apprehend': 0, 'apprehension': 0, 'apprehensive': 0, 'apprentice': 0, 'apprenticeship': 0, 'approach': 0, 'approaching': 0, 'approbation': 1, 'appropriation': 0, 'approval': 1, 'approve': 1, 'approving': 1, 'approximate': 0, 'approximately': 0, 'approximating': 0, 'approximation': 0, 'appurtenances': 0, 'apron': 0, 'apt': 1, 'aptitude': 1, 'aqua': 0, 'aquamarine': 0, 'aquarium': 0, 'aquatic': 0, 'aqueduct': 0, 'aqueous': 0, 'arable': 0, 'arbiter': 0, 'arbitrate': 0, 'arbitration': 0, 'arbitrator': 0, 'arbor': 0, 'arc': 0, 'arcade': 0, 'arch': 0, 'archaeological': 0, 'archaeologist': 0, 'archaeology': 1, 'archaic': 0, 'archbishop': 0, 'arched': 0, 'archer': 0, 'archery': 0, 'archetype': 0, 'archipelago': 0, 'architect': 0, 'architecture': 0, 'archive': 0, 'arctic': 0, 'ardent': 1, 'ardor': 1, 'arduous': 0, 'area': 0, 'arena': 0, 'areola': 0, 'argent': 0, 'argue': 0, 'argument': 0, 'argumentation': 0, 'argumentative': 0, 'arguments': 0, 'arid': 0, 'aristocracy': 1, 'aristocrat': 0, 'aristocratic': 1, 'arithmetic': 0, 'ark': 0, 'arm': 0, 'armada': 0, 'armament': 0, 'armaments': 0, 'armature': 0, 'armed': 1, 'armor': 1, 'armored': 0, 'armory': 0, 'arms': 0, 'army': 0, 'aroma': 1, 'arousal': 0, 'arouse': 1, 'arraignment': 0, 'arrange': 0, 'arranged': 0, 'arrangement': 0, 'array': 1, 'arrears': 0, 'arrest': 0, 'arrival': 0, 'arrive': 0, 'arrogance': 0, 'arrogant': 0, 'arrow': 0, 'arsenal': 0, 'arsenic': 0, 'arson': 0, 'art': 1, 'artery': 0, 'artful': 0, 'arthropod': 0, 'artichoke': 0, 'article': 0, 'articles': 0, 'articulate': 1, 'articulation': 1, 'artifice': 0, 'artillery': 0, 'artisan': 1, 'artist': 0, 'artiste': 1, 'artistic': 1, 'artists': 0, 'ascend': 0, 'ascendancy': 1, 'ascension': 0, 'ascent': 1, 'ascertain': 0, 'ascertained': 0, 'ascetic': 0, 'ash': 0, 'ashamed': 0, 'ashes': 0, 'asleep': 0, 'asp': 0, 'aspartame': 0, 'aspect': 0, 'aspects': 0, 'asphalt': 0, 'aspiration': 1, 'aspire': 1, 'aspiring': 1, 'ass': 0, 'assail': 0, 'assailant': 0, 'assassin': 0, 'assassinate': 0, 'assassination': 0, 'assault': 0, 'assay': 0, 'assemblage': 0, 'assemble': 0, 'assembled': 0, 'assembly': 1, 'assent': 1, 'assert': 0, 'asserting': 1, 'assertion': 0, 'assess': 0, 'assessment': 0, 'assessor': 0, 'assets': 1, 'asshole': 0, 'assign': 0, 'assignee': 0, 'assignment': 0, 'assimilate': 0, 'assimilation': 0, 'assist': 1, 'assistance': 1, 'assistant': 0, 'associate': 1, 'association': 0, 'assorted': 0, 'assortment': 0, 'assuage': 1, 'assumed': 0, 'assuming': 0, 'assumption': 0, 'assurance': 1, 'assure': 0, 'assured': 1, 'assuredly': 0, 'asterisk': 0, 'asteroids': 0, 'astigmatism': 0, 'astonishingly': 1, 'astonishment': 1, 'astral': 0, 'astray': 0, 'astringent': 0, 'astrologer': 1, 'astrology': 0, 'astronaut': 1, 'astronomer': 1, 'astronomy': 0, 'astute': 1, 'asunder': 0, 'asylum': 0, 'asymmetric': 0, 'asymmetry': 0, 'asymptotic': 0, 'atelier': 0, 'atheism': 0, 'atheist': 0, 'atheistic': 0, 'atherosclerosis': 0, 'athlete': 1, 'athletic': 1, 'athleticism': 0, 'athletics': 0, 'atlas': 0, 'atmosphere': 0, 'atmospheric': 0, 'atoll': 0, 'atom': 1, 'atomic': 0, 'atone': 1, 'atonement': 1, 'atrium': 0, 'atrocious': 0, 'atrocity': 0, 'atrophy': 0, 'attach': 0, 'attachment': 1, 'attack': 0, 'attacking': 0, 'attain': 0, 'attainable': 1, 'attainment': 1, 'attempt': 0, 'attendance': 0, 'attendant': 1, 'attention': 1, 'attentive': 1, 'attenuate': 0, 'attenuated': 0, 'attenuation': 0, 'attest': 1, 'attestation': 0, 'attic': 0, 'attire': 0, 'attitude': 0, 'attorney': 1, 'attraction': 1, 'attractiveness': 1, 'attributable': 0, 'attribute': 0, 'attribution': 0, 'attrition': 0, 'auburn': 0, 'auction': 0, 'auctioneer': 0, 'audacious': 0, 'audacity': 0, 'audible': 0, 'audience': 0, 'audit': 0, 'audition': 0, 'auditor': 0, 'auditorium': 0, 'auditory': 0, 'aught': 0, 'augment': 1, 'augmentation': 0, 'august': 1, 'aunt': 1, 'aura': 1, 'aurora': 0, 'auspices': 0, 'auspicious': 1, 'austere': 0, 'austerity': 0, 'authentic': 1, 'authenticate': 0, 'authentication': 0, 'authenticity': 1, 'author': 1, 'authoritative': 1, 'authority': 1, 'authorization': 1, 'authorize': 0, 'authorized': 1, 'authorship': 0, 'auto': 0, 'autobiography': 0, 'autocratic': 0, 'autograph': 0, 'automatic': 0, 'automobile': 0, 'autonomy': 0, 'autopsy': 0, 'autumn': 0, 'auxiliary': 0, 'avail': 0, 'avalanche': 0, 'avarice': 0, 'avatar': 1, 'avenger': 0, 'avenue': 0, 'aver': 0, 'average': 0, 'averse': 0, 'aversion': 0, 'avert': 0, 'aviary': 0, 'aviation': 0, 'aviator': 0, 'avid': 0, 'avocado': 0, 'avoid': 0, 'avoidance': 0, 'avoiding': 0, 'await': 0, 'awake': 0, 'awaken': 0, 'award': 1, 'awe': 0, 'awful': 0, 'awkwardness': 0, 'awning': 0, 'awry': 0, 'axial': 0, 'axiom': 0, 'axiomatic': 0, 'axis': 0, 'axle': 0, 'ay': 1, 'aye': 1, 'azimuth': 0, 'azure': 0, 'babble': 0, 'babbling': 0, 'baboon': 0, 'baby': 1, 'babysitter': 0, 'baccalaureate': 1, 'baccarat': 0, 'bachelor': 0, 'back': 0, 'backbone': 1, 'backer': 0, 'backfire': 0, 'backgammon': 0, 'background': 0, 'backhoe': 0, 'backpacker': 0, 'backtrack': 0, 'backward': 0, 'backwards': 0, 'backwater': 0, 'bacteria': 0, 'bacterium': 0, 'bad': 0, 'badge': 0, 'badger': 0, 'badly': 0, 'badness': 0, 'baffle': 0, 'bag': 0, 'baggage': 0, 'baggy': 0, 'bagpipes': 0, 'bail': 0, 'bailiff': 0, 'bait': 0, 'bake': 0, 'bakery': 0, 'baking': 0, 'bal': 0, 'balance': 1, 'balanced': 1, 'balcony': 0, 'bald': 0, 'bale': 0, 'balk': 0, 'ball': 0, 'ballad': 1, 'ballast': 0, 'ballet': 1, 'balloon': 0, 'ballot': 1, 'ballroom': 0, 'balm': 1, 'balmy': 0, 'balsam': 1, 'balsamic': 0, 'ban': 0, 'banana': 0, 'band': 0, 'bandage': 0, 'bandit': 0, 'bandwagon': 0, 'bane': 0, 'bang': 0, 'banger': 0, 'banish': 0, 'banished': 0, 'banishment': 0, 'banjo': 0, 'bank': 0, 'banker': 0, 'bankrupt': 0, 'bankruptcy': 0, 'banner': 0, 'banquet': 1, 'banshee': 0, 'banter': 0, 'baptism': 1, 'baptismal': 1, 'bar': 0, 'barb': 0, 'barbarian': 0, 'barbaric': 0, 'barbarism': 0, 'barbecue': 0, 'barbed': 0, 'bard': 1, 'bareback': 0, 'barefoot': 0, 'barely': 0, 'barf': 0, 'bargain': 1, 'barge': 0, 'baritone': 0, 'bark': 0, 'barn': 0, 'barney': 0, 'barometer': 0, 'baron': 0, 'baroque': 0, 'barrack': 0, 'barred': 0, 'barrel': 0, 'barren': 0, 'barricade': 0, 'barrier': 0, 'barring': 0, 'barrister': 0, 'barrow': 0, 'bartender': 0, 'barter': 0, 'base': 0, 'baseball': 0, 'baseboard': 0, 'baseless': 0, 'basement': 0, 'basilica': 0, 'basin': 0, 'basis': 0, 'bask': 0, 'basket': 0, 'basketball': 1, 'bass': 0, 'basso': 0, 'bassoon': 0, 'bastard': 0, 'bastion': 1, 'bat': 0, 'batch': 0, 'batching': 0, 'bate': 0, 'bath': 1, 'bathe': 0, 'bathroom': 0, 'bathymetry': 0, 'baton': 0, 'battalion': 0, 'batter': 0, 'battered': 0, 'battery': 0, 'battle': 0, 'battled': 0, 'battlefield': 0, 'bawdy': 0, 'bay': 0, 'bayonet': 0, 'bayou': 0, 'bazaar': 0, 'beach': 0, 'beacon': 0, 'bead': 0, 'beading': 0, 'beads': 0, 'beagle': 0, 'beak': 0, 'beaker': 0, 'beam': 1, 'beaming': 1, 'bear': 0, 'beard': 0, 'bearded': 0, 'bearer': 0, 'bearing': 0, 'bearings': 0, 'bearish': 0, 'beast': 0, 'beastly': 0, 'beat': 0, 'beating': 0, 'beau': 0, 'beautification': 1, 'beautiful': 1, 'beautify': 1, 'beauty': 1, 'beck': 0, 'beckon': 0, 'bed': 0, 'bedding': 0, 'bedrock': 1, 'bedroom': 0, 'bedtime': 0, 'bee': 0, 'beef': 0, 'beehive': 0, 'beer': 1, 'beeswax': 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'wheels': 0, 'whereabouts': 0, 'wherefore': 0, 'wherewith': 0, 'wherewithal': 0, 'whet': 0, 'whiff': 0, 'whilst': 0, 'whim': 0, 'whimper': 0, 'whimsical': 0, 'whimsy': 0, 'whine': 0, 'whip': 0, 'whirl': 0, 'whirlpool': 0, 'whirlwind': 0, 'whisk': 0, 'whisker': 0, 'whisky': 0, 'whisper': 0, 'whispered': 0, 'whistle': 0, 'whit': 0, 'white': 1, 'whiteness': 1, 'whitish': 0, 'whiz': 0, 'wholesome': 1, 'wholly': 0, 'whoop': 0, 'whopping': 0, 'whore': 0, 'wick': 0, 'wicked': 0, 'wickedness': 0, 'wicker': 0, 'wicket': 1, 'wide': 0, 'widely': 0, 'widen': 0, 'widespread': 1, 'widow': 0, 'widower': 0, 'width': 0, 'wield': 0, 'wife': 0, 'wig': 0, 'wight': 0, 'wild': 0, 'wildcat': 0, 'wilderness': 0, 'wildfire': 0, 'willful': 0, 'willingly': 1, 'willingness': 1, 'willow': 0, 'wilted': 0, 'wily': 0, 'wimp': 0, 'wimpy': 0, 'wince': 0, 'winch': 0, 'wind': 0, 'windfall': 1, 'winding': 0, 'windmill': 0, 'window': 0, 'windy': 0, 'wine': 0, 'wing': 0, 'winged': 0, 'wink': 0, 'winner': 1, 'winning': 1, 'winnings': 1, 'winter': 0, 'wintry': 0, 'wipe': 0, 'wire': 0, 'wireless': 1, 'wis': 1, 'wisdom': 1, 'wise': 1, 'wishful': 0, 'wistful': 0, 'wit': 1, 'witch': 0, 'witchcraft': 0, 'withal': 0, 'withdraw': 0, 'withdrawal': 0, 'wither': 0, 'withered': 0, 'withstand': 1, 'witness': 0, 'wits': 1, 'witty': 1, 'wizard': 1, 'woe': 0, 'woeful': 0, 'woefully': 0, 'woman': 0, 'womanhood': 0, 'womanly': 0, 'womb': 1, 'wonderful': 1, 'wonderfully': 1, 'wondrous': 1, 'wont': 0, 'woo': 0, 'wood': 0, 'woodcut': 0, 'wooden': 0, 'woodlands': 0, 'woody': 0, 'wooing': 0, 'wool': 0, 'woolly': 0, 'wop': 0, 'word': 1, 'wording': 0, 'words': 0, 'wordy': 0, 'work': 0, 'workbook': 0, 'worker': 0, 'working': 1, 'workman': 0, 'workmanship': 0, 'workplace': 0, 'works': 0, 'workshop': 0, 'world': 0, 'worldly': 0, 'worldwide': 0, 'worm': 0, 'worn': 0, 'worried': 0, 'worry': 0, 'worrying': 0, 'worse': 0, 'worsening': 0, 'worship': 1, 'worth': 1, 'worthless': 0, 'worthy': 1, 'wot': 1, 'wound': 0, 'wrangler': 0, 'wrangling': 0, 'wrap': 0, 'wrapper': 0, 'wrapping': 0, 'wrath': 0, 'wreak': 0, 'wreath': 0, 'wreck': 0, 'wrecked': 0, 'wrench': 0, 'wrest': 0, 'wrestle': 0, 'wrestler': 0, 'wrestling': 0, 'wretch': 0, 'wretched': 0, 'wright': 0, 'wring': 0, 'wrinkle': 0, 'wrinkled': 0, 'wrist': 0, 'wristband': 0, 'wristwatch': 0, 'writ': 0, 'write': 0, 'writer': 1, 'writing': 0, 'written': 0, 'wrong': 0, 'wrongdoing': 0, 'wrongful': 0, 'wrongly': 0, 'wrought': 0, 'wry': 0, 'xenophobia': 0, 'xerox': 0, 'yacht': 0, 'yachting': 0, 'yak': 0, 'yam': 0, 'yank': 0, 'yard': 0, 'yarn': 0, 'yaw': 0, 'yawn': 0, 'yawning': 0, 'yea': 0, 'year': 0, 'yearbook': 0, 'yearling': 0, 'yearly': 0, 'yearn': 0, 'yearning': 1, 'years': 0, 'yeast': 0, 'yell': 0, 'yellow': 0, 'yellows': 0, 'yelp': 0, 'yeoman': 0, 'yesterday': 0, 'yesteryear': 0, 'yew': 0, 'yield': 0, 'yielding': 0, 'yogi': 0, 'yoke': 0, 'yolk': 0, 'yon': 0, 'yonder': 0, 'young': 1, 'younger': 1, 'youth': 1, 'zany': 0, 'zap': 0, 'zeal': 1, 'zealot': 0, 'zealous': 1, 'zebra': 0, 'zenith': 0, 'zephyr': 0, 'zeppelin': 0, 'zest': 1, 'zip': 0, 'zodiac': 0, 'zone': 0, 'zoo': 0, 'zoological': 0, 'zoology': 0, 'zoom': 0}
#Get the words to be scored by lexicon
corpus = df_new['word_final'].values
corpus[0:5]
array(['case id worst poor customer service giving response day register complaint call disconnected call without giving proper answer way reach customer support tried never change review',
'please dont install app people stole information related buying pattern card detail phone pay detail toosame happened today try make fool give peculiar notification phonepay pay think install',
'dont waste time money woohoo payment successful gift card refund day customer care clue response raised req mar response last day',
'worst customer supportthey wont pick call wont respond mail twice amount deducted status showing failed twice amount deducted status showing processing yet received voucher even received kyc call well',
'happy customer till faced error guess even dont reply query mail worst service support request id kuch sharm kro saalo'],
dtype=object)
#For each record
#For each word in record
#Get the word score (score is a number if the word is in Lexicon, 0 if not)
#Add all the scores and find the ploarity
positivenrc = []
strength =[]
for record in corpus:
#print("record", record)
score = 0
words = record.replace("'","").lower().split()
for word in words:
#print("word", word)
if word in (lexicons):
score = score + lexicons[word]
#print("score",score)
strength.append(score)
#print('strength',strength)
if (score > 0):
positivenrc.append('1')
else:
positivenrc.append('0')
#else:
# prediction.append('neutral')
print(positivenrc)
#print(prediction)
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df_new['positivenrc']= positivenrc
df_new.head()
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | tokenized_docs_no_stopwords | preprocessed_docs | word_final | strength_affin | prediction_affin | positivenrc | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | case id worst poor customer service giving res... | -2 | negative | 1 |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | ['please', 'dont', 'install', 'this', 'app', '... | ['please', 'dont', 'install', 'app', 'people',... | ['please', 'dont', 'install', 'app', 'people',... | please dont install app people stole informati... | -3 | negative | 1 |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... | ['dont', 'waste', 'your', 'time', 'and', 'mone... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | dont waste time money woohoo payment successfu... | 9 | positive | 1 |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | worst customer supportthey wont pick call wont... | -5 | negative | 1 |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... | ['was', 'a', 'happy', 'customer', 'till', 'i',... | ['happy', 'customer', 'till', 'faced', 'error'... | ['happy', 'customer', 'till', 'faced', 'error'... | happy customer till faced error guess even don... | 0 | neutral | 1 |
#Read the lexicon file
lex_file = open("D:\\11 Project\\Project\\NRC_file - Negative.csv")
lexicons = {}
records = lex_file.readlines()
for record in records:
#print(record) # line contains newline charecter
#print(record.rstrip('\n').split(",")) - to remove new line charecter
lexicons[record.rstrip('\n').split(",")[0]] = int(record.rstrip('\n').split(",")[1])
print(lexicons)
{'aback': 0, 'abacus': 0, 'abandon': 1, 'abandoned': 1, 'abandonment': 1, 'abate': 0, 'abatement': 0, 'abba': 0, 'abbot': 0, 'abbreviate': 0, 'abbreviation': 0, 'abdomen': 0, 'abdominal': 0, 'abduction': 1, 'aberrant': 1, 'aberration': 1, 'abeyance': 0, 'abhor': 1, 'abhorrent': 1, 'abide': 0, 'ability': 0, 'abject': 1, 'ablation': 0, 'ablaze': 0, 'abnormal': 1, 'aboard': 0, 'abode': 0, 'abolish': 1, 'abolition': 1, 'abominable': 1, 'abomination': 1, 'aboriginal': 0, 'abort': 1, 'abortion': 1, 'abortive': 1, 'abound': 0, 'abovementioned': 0, 'abrasion': 1, 'abroad': 0, 'abrogate': 1, 'abrupt': 0, 'abruptly': 0, 'abscess': 1, 'absence': 1, 'absent': 1, 'absentee': 1, 'absenteeism': 1, 'absinthe': 0, 'absolute': 0, 'absolution': 0, 'absorbed': 0, 'absorbent': 0, 'absorbing': 0, 'absorption': 0, 'abstain': 0, 'abstention': 0, 'abstinence': 0, 'abstract': 0, 'abstraction': 0, 'absurd': 1, 'absurdity': 1, 'abundance': 1, 'abundant': 0, 'abuse': 1, 'abutment': 0, 'aby': 0, 'abysmal': 1, 'abyss': 1, 'academic': 0, 'academy': 0, 'accede': 0, 'accelerate': 0, 'acceleration': 0, 'accent': 0, 'accentuate': 0, 'accept': 0, 'acceptable': 0, 'acceptance': 0, 'access': 0, 'accessible': 0, 'accession': 0, 'accessory': 0, 'accident': 1, 'accidental': 1, 'accidentally': 0, 'accolade': 0, 'accommodate': 0, 'accommodation': 0, 'accompaniment': 0, 'accompany': 0, 'accompanying': 0, 'accomplice': 0, 'accomplish': 0, 'accomplished': 0, 'accomplishment': 0, 'accord': 0, 'accordance': 0, 'accordion': 0, 'account': 0, 'accountability': 0, 'accountable': 0, 'accountant': 0, 'accounting': 0, 'accounts': 0, 'accredited': 0, 'accretion': 0, 'accrue': 0, 'accueil': 0, 'accumulate': 0, 'accumulation': 0, 'accuracy': 0, 'accurate': 0, 'accursed': 1, 'accusation': 1, 'accusative': 1, 'accused': 1, 'accuser': 1, 'accusing': 1, 'accustomed': 0, 'ace': 0, 'acetic': 0, 'ache': 1, 'achieve': 0, 'achievement': 0, 'aching': 1, 'acid': 1, 'acidity': 0, 'acknowledge': 0, 'acknowledged': 0, 'acknowledgment': 0, 'acme': 0, 'acoustic': 0, 'acoustics': 0, 'acquaint': 0, 'acquaintance': 0, 'acquainted': 0, 'acquiescence': 0, 'acquire': 0, 'acquiring': 0, 'acquisition': 0, 'acquisitions': 0, 'acreage': 0, 'acres': 0, 'acrobat': 0, 'act': 0, 'acting': 0, 'action': 0, 'actionable': 1, 'active': 0, 'activity': 0, 'actor': 0, 'actual': 0, 'actuality': 0, 'actuary': 0, 'acuity': 0, 'acumen': 0, 'acupuncture': 0, 'acutely': 0, 'adage': 0, 'adamant': 0, 'adapt': 0, 'adaptable': 0, 'add': 0, 'added': 0, 'addendum': 0, 'adder': 1, 'addiction': 1, 'addition': 0, 'additional': 0, 'additive': 0, 'address': 0, 'addressee': 0, 'addresses': 0, 'adept': 0, 'adequacy': 0, 'adequate': 0, 'adhere': 0, 'adherence': 0, 'adherent': 0, 'adhering': 0, 'adhesion': 0, 'adhesive': 0, 'adieu': 0, 'adipose': 1, 'adjacency': 0, 'adjacent': 0, 'adjective': 0, 'adjoining': 0, 'adjourn': 0, 'adjournment': 0, 'adjudicate': 1, 'adjudication': 0, 'adjunct': 0, 'adjust': 0, 'adjustment': 0, 'adjuvant': 0, 'administer': 0, 'administration': 0, 'administrative': 0, 'admirable': 0, 'admiral': 0, 'admiralty': 0, 'admiration': 0, 'admire': 0, 'admirer': 0, 'admissibility': 0, 'admissible': 0, 'admission': 0, 'admit': 0, 'admittance': 0, 'admitted': 0, 'admitting': 0, 'admixture': 0, 'admonition': 1, 'ado': 0, 'adobe': 0, 'adolescence': 0, 'adolescent': 0, 'adopt': 0, 'adoption': 0, 'adorable': 0, 'adoration': 0, 'adore': 0, 'adorn': 0, 'adornment': 0, 'adrift': 1, 'adult': 0, 'adulterated': 1, 'adultery': 1, 'advance': 0, 'advanced': 0, 'advancement': 0, 'advancing': 0, 'advantage': 0, 'advantageous': 0, 'advent': 0, 'adventure': 0, 'adventurer': 0, 'adventurous': 0, 'adversary': 1, 'adverse': 1, 'adversity': 1, 'advertise': 0, 'advertisement': 0, 'advice': 0, 'advisable': 0, 'advise': 0, 'advised': 0, 'advisement': 0, 'adviser': 0, 'advocacy': 0, 'advocate': 0, 'aegis': 0, 'aeration': 0, 'aerial': 0, 'aerodrome': 0, 'aerodynamics': 0, 'aeronautics': 0, 'aeroplane': 0, 'aesthetic': 0, 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'unattached': 1, 'unattainable': 1, 'unattended': 0, 'unattractive': 1, 'unauthorized': 1, 'unavoidable': 1, 'unaware': 1, 'unbalanced': 0, 'unbearable': 1, 'unbeaten': 1, 'unbelief': 1, 'unbelievable': 1, 'unbiased': 0, 'unborn': 1, 'unbound': 0, 'unbounded': 0, 'unbreakable': 0, 'unbridled': 1, 'unbroken': 0, 'uncanny': 1, 'uncaring': 1, 'uncertain': 1, 'uncertainty': 0, 'unchallenged': 0, 'unchangeable': 1, 'unchanged': 0, 'unclaimed': 0, 'uncle': 0, 'unclean': 1, 'uncomfortable': 1, 'uncommon': 0, 'uncommonly': 0, 'uncompromising': 0, 'unconcerned': 0, 'unconfirmed': 0, 'unconnected': 0, 'unconscionable': 1, 'unconscious': 1, 'unconsciousness': 0, 'unconstitutional': 1, 'unconstrained': 0, 'uncontested': 0, 'uncontrollable': 1, 'uncontrolled': 1, 'unconventional': 0, 'unconvinced': 0, 'uncooked': 0, 'uncorrelated': 0, 'uncover': 0, 'uncritical': 0, 'uncut': 0, 'undecided': 1, 'undefined': 0, 'undeniable': 0, 'undercover': 0, 'undercurrent': 0, 'underestimate': 0, 'undergo': 0, 'undergraduate': 0, 'underground': 0, 'underlie': 0, 'underline': 0, 'undermined': 1, 'underneath': 0, 'underpaid': 1, 'underpants': 0, 'underscore': 0, 'undersized': 1, 'understanding': 0, 'understood': 0, 'undertake': 0, 'undertaker': 0, 'undertaking': 0, 'underwood': 0, 'underwrite': 0, 'underwriter': 0, 'undeserved': 0, 'undesirable': 1, 'undesired': 1, 'undeveloped': 0, 'undirected': 0, 'undisclosed': 0, 'undiscovered': 0, 'undisputed': 0, 'undisturbed': 0, 'undivided': 0, 'undo': 1, 'undoing': 0, 'undoubted': 0, 'undress': 0, 'undressed': 0, 'undue': 0, 'undying': 0, 'unearned': 0, 'unearth': 0, 'uneasiness': 1, 'uneasy': 1, 'uneducated': 1, 'unemployed': 1, 'unencumbered': 0, 'unending': 0, 'unequal': 1, 'unequalled': 0, 'unequivocal': 0, 'unequivocally': 0, 'uneven': 1, 'uneventful': 0, 'unexpected': 1, 'unexpectedly': 0, 'unexplained': 1, 'unexplored': 0, 'unfailing': 0, 'unfair': 1, 'unfairness': 1, 'unfaithful': 1, 'unfamiliar': 0, 'unfavorable': 1, 'unfettered': 0, 'unfinished': 1, 'unflinching': 0, 'unfold': 0, 'unforeseen': 0, 'unforgiving': 1, 'unfortunate': 1, 'unfriendly': 1, 'unfulfilled': 1, 'unfurnished': 1, 'ungodly': 1, 'ungrateful': 1, 'unguarded': 0, 'unhappiness': 1, 'unhappy': 1, 'unharmed': 0, 'unhealthy': 1, 'unhindered': 0, 'unholy': 1, 'unicorn': 0, 'unification': 0, 'uniform': 0, 'uniformity': 0, 'uniformly': 0, 'unimaginable': 1, 'unimportant': 1, 'unimpressed': 1, 'unimproved': 1, 'uninfected': 0, 'uninformed': 1, 'uninhabited': 0, 'uninitiated': 1, 'uninspired': 1, 'unintelligible': 1, 'unintended': 0, 'unintentional': 0, 'unintentionally': 1, 'uninterested': 1, 'uninteresting': 1, 'uninterrupted': 0, 'uninvited': 0, 'union': 0, 'unique': 0, 'unison': 0, 'unit': 0, 'unitary': 0, 'unite': 0, 'united': 0, 'unity': 0, 'universal': 0, 'universality': 0, 'universe': 0, 'university': 0, 'unjust': 1, 'unjustifiable': 1, 'unjustified': 1, 'unkind': 1, 'unknowable': 0, 'unknown': 1, 'unlawful': 1, 'unleash': 0, 'unlicensed': 1, 'unlike': 0, 'unlimited': 0, 'unload': 0, 'unloaded': 0, 'unlock': 0, 'unlucky': 1, 'unmanageable': 1, 'unmarked': 0, 'unmarried': 0, 'unmask': 0, 'unmatched': 0, 'unmistakable': 0, 'unmitigated': 0, 'unmoved': 0, 'unnamed': 0, 'unnatural': 1, 'unnecessary': 0, 'unneeded': 0, 'unnoticed': 0, 'unnumbered': 0, 'unobserved': 0, 'unobstructed': 0, 'unobtrusive': 0, 'unoccupied': 0, 'unofficial': 1, 'unopened': 0, 'unopposed': 0, 'unordered': 0, 'unorganized': 0, 'unorthodox': 0, 'unpack': 0, 'unpaid': 1, 'unpleasant': 1, 'unpopular': 1, 'unprecedented': 0, 'unpredictable': 1, 'unprepared': 1, 'unpretentious': 0, 'unproductive': 1, 'unprofitable': 1, 'unprotected': 1, 'unproven': 0, 'unpublished': 1, 'unquestionable': 0, 'unquestionably': 0, 'unquestioned': 0, 'unread': 0, 'unreal': 0, 'unrealistic': 0, 'unrecorded': 0, 'unregistered': 0, 'unregulated': 0, 'unrelated': 0, 'unrelenting': 0, 'unreliable': 1, 'unrepentant': 0, 'unrequited': 1, 'unresolved': 0, 'unrest': 0, 'unrestrained': 0, 'unrestricted': 0, 'unruly': 1, 'unsafe': 1, 'unsatisfactory': 1, 'unsatisfied': 1, 'unsavory': 1, 'unscathed': 0, 'unscientific': 0, 'unscrupulous': 1, 'unseat': 0, 'unseen': 0, 'unselfish': 0, 'unsettled': 1, 'unsightly': 1, 'unsophisticated': 1, 'unspeakable': 1, 'unspecified': 0, 'unstable': 1, 'unsteady': 0, 'unsuccessful': 1, 'unsuitable': 1, 'unsung': 1, 'unsupported': 1, 'unsurpassed': 0, 'unsuspecting': 0, 'unsustainable': 1, 'unsweetened': 0, 'unsympathetic': 1, 'untamed': 1, 'untenable': 1, 'untested': 0, 'unthinkable': 1, 'untidy': 1, 'untie': 1, 'untimely': 1, 'untitled': 1, 'untold': 1, 'untouched': 0, 'untoward': 1, 'untrained': 1, 'untranslated': 0, 'untrue': 1, 'untrustworthy': 1, 'unused': 0, 'unusual': 0, 'unusually': 0, 'unveil': 0, 'unveiling': 0, 'unverified': 0, 'unwarranted': 1, 'unwary': 0, 'unwashed': 1, 'unwavering': 0, 'unwelcome': 1, 'unwell': 1, 'unwilling': 0, 'unwillingly': 0, 'unwillingness': 1, 'unwind': 0, 'unwise': 1, 'unwitting': 1, 'unwittingly': 0, 'unworthy': 1, 'unwritten': 0, 'unyielding': 1, 'upheaval': 1, 'uphill': 1, 'upholstery': 0, 'upland': 0, 'uplands': 0, 'uplift': 0, 'upper': 0, 'upright': 0, 'uprising': 1, 'uproar': 1, 'upset': 1, 'upshot': 0, 'upstairs': 0, 'upstart': 0, 'upwards': 0, 'uranium': 0, 'urban': 0, 'urchin': 1, 'urge': 0, 'urgency': 0, 'urgent': 1, 'urinalysis': 0, 'urn': 0, 'usage': 0, 'usefully': 0, 'usefulness': 0, 'useless': 1, 'usher': 0, 'usual': 0, 'usurp': 1, 'usurped': 1, 'usury': 1, 'utensil': 0, 'utilitarian': 0, 'utility': 0, 'utilization': 0, 'utilize': 0, 'utmost': 0, 'utopian': 0, 'utterance': 0, 'utterly': 0, 'vacancy': 1, 'vacation': 0, 'vaccination': 0, 'vaccine': 0, 'vacuolar': 0, 'vacuole': 0, 'vacuous': 1, 'vacuum': 0, 'vague': 1, 'vagueness': 1, 'vainly': 1, 'valance': 0, 'vale': 0, 'valet': 0, 'valiant': 0, 'validity': 0, 'valley': 0, 'valor': 0, 'valuable': 0, 'valuation': 0, 'valve': 0, 'vamp': 0, 'vampire': 1, 'van': 0, 'vane': 0, 'vanguard': 0, 'vanilla': 0, 'vanish': 0, 'vanished': 1, 'vanity': 1, 'vanquish': 0, 'vapor': 0, 'vara': 0, 'variable': 0, 'variance': 0, 'variation': 0, 'variations': 0, 'varicella': 1, 'varicose': 1, 'varied': 0, 'variegated': 0, 'variety': 0, 'vary': 0, 'vascular': 0, 'vase': 0, 'vast': 0, 'vat': 0, 'vaudeville': 0, 'vault': 0, 'vaulted': 0, 'vaulting': 0, 'veal': 0, 'vector': 0, 'veer': 0, 'vega': 0, 'vegetable': 0, 'vegetarian': 0, 'vegetarianism': 0, 'vegetation': 0, 'vegetative': 1, 'vehement': 1, 'vehicle': 0, 'veil': 0, 'veiled': 0, 'vein': 0, 'veined': 0, 'vellum': 0, 'velocity': 0, 'velour': 0, 'velvet': 0, 'velvety': 0, 'vena': 0, 'vendetta': 1, 'vendor': 0, 'veneer': 0, 'venerable': 0, 'veneration': 0, 'vengeance': 1, 'vengeful': 1, 'venison': 0, 'venom': 1, 'venomous': 1, 'venous': 0, 'vent': 0, 'ventilation': 0, 'ventilator': 0, 'ventricle': 0, 'ventricular': 0, 'venture': 0, 'venue': 0, 'veracity': 0, 'veranda': 0, 'verbal': 0, 'verbatim': 0, 'verbiage': 0, 'verbose': 0, 'verbosity': 1, 'verdant': 0, 'verdict': 0, 'verge': 1, 'verification': 0, 'verified': 0, 'verify': 0, 'verily': 0, 'veritable': 0, 'vermin': 1, 'vernacular': 0, 'vernal': 0, 'veronica': 0, 'versatile': 0, 'versatility': 0, 'verse': 0, 'version': 0, 'versus': 1, 'vert': 0, 'vertebra': 0, 'vertebral': 0, 'vertex': 0, 'vertical': 0, 'vertically': 0, 'vertigo': 1, 'verve': 0, 'vesicle': 0, 'vesicular': 0, 'vessel': 0, 'vest': 0, 'vested': 0, 'vestibule': 0, 'vestige': 0, 'vet': 0, 'veteran': 0, 'veterinarian': 0, 'veto': 1, 'viability': 0, 'viable': 0, 'viaduct': 0, 'vial': 0, 'vibrate': 0, 'vibration': 0, 'vibratory': 0, 'vicar': 0, 'vicarious': 0, 'vice': 1, 'vicinity': 0, 'vicious': 1, 'victim': 1, 'victimized': 1, 'victor': 0, 'victoria': 0, 'victorious': 0, 'victory': 0, 'videotape': 0, 'vie': 0, 'view': 0, 'vigil': 0, 'vigilance': 0, 'vigilant': 0, 'vignette': 0, 'vigor': 0, 'vigorous': 0, 'viking': 0, 'villa': 0, 'village': 0, 'villager': 0, 'villain': 1, 'villainous': 1, 'vinaigrette': 0, 'vindicate': 0, 'vindicated': 0, 'vindication': 0, 'vindictive': 1, 'vinegar': 0, 'vineyard': 0, 'viola': 0, 'violation': 1, 'violence': 1, 'violent': 1, 'violently': 1, 'violet': 0, 'violin': 0, 'violinist': 0, 'viper': 1, 'virgin': 0, 'virginity': 0, 'virology': 0, 'virtual': 0, 'virtually': 0, 'virtue': 0, 'virtuoso': 0, 'virtuous': 0, 'virulence': 1, 'virus': 1, 'visa': 0, 'visage': 0, 'viscosity': 0, 'viscous': 0, 'vise': 0, 'visibility': 0, 'visible': 0, 'visibly': 0, 'vision': 0, 'visionary': 0, 'visit': 0, 'visitation': 1, 'visiting': 0, 'visitor': 0, 'visor': 0, 'vista': 0, 'visual': 0, 'visualize': 0, 'vital': 0, 'vitality': 0, 'vitreous': 0, 'vivacious': 0, 'vivid': 0, 'vixen': 1, 'vocabulary': 0, 'vocal': 0, 'vocalist': 0, 'vocation': 0, 'vogue': 0, 'voice': 0, 'voiceless': 0, 'void': 0, 'volatility': 1, 'volcanic': 0, 'volcano': 1, 'volition': 0, 'volley': 0, 'voltmeter': 0, 'volume': 0, 'voluminous': 0, 'voluntarily': 0, 'voluntary': 0, 'volunteer': 0, 'volunteering': 0, 'volunteers': 0, 'voluptuous': 0, 'vomit': 0, 'vomiting': 1, 'voodoo': 1, 'voracious': 0, 'vortex': 0, 'vote': 1, 'voting': 0, 'votive': 0, 'vouch': 0, 'voucher': 0, 'vow': 0, 'vowel': 0, 'voyage': 0, 'voyager': 0, 'vulgar': 1, 'vulgarity': 1, 'vulnerability': 1, 'vulnerable': 0, 'vulture': 1, 'wad': 0, 'wade': 0, 'wafer': 0, 'waffle': 1, 'wag': 0, 'wager': 0, 'wages': 0, 'wagon': 0, 'wail': 1, 'waist': 0, 'waistcoat': 0, 'wait': 1, 'waiter': 0, 'waiting': 0, 'waive': 0, 'wake': 0, 'walk': 0, 'walker': 0, 'wall': 0, 'wallet': 0, 'wallow': 1, 'walnut': 0, 'waltz': 0, 'wan': 1, 'wand': 0, 'wander': 0, 'wanderer': 0, 'wandering': 0, 'wane': 1, 'waning': 0, 'wanting': 1, 'war': 1, 'warbler': 0, 'ward': 0, 'warden': 1, 'wardrobe': 0, 'ware': 1, 'warehouse': 0, 'warfare': 1, 'warlike': 1, 'warlock': 0, 'warming': 0, 'warn': 1, 'warned': 0, 'warning': 0, 'warp': 1, 'warped': 1, 'warrant': 0, 'warranted': 0, 'warrants': 0, 'warranty': 0, 'warren': 0, 'warrior': 0, 'wart': 1, 'wary': 0, 'wash': 0, 'washing': 0, 'washout': 0, 'wasp': 0, 'waste': 1, 'wasted': 1, 'wasteful': 1, 'wasting': 1, 'watch': 0, 'watchdog': 0, 'watchful': 0, 'watchman': 0, 'water': 0, 'watercourse': 0, 'watered': 0, 'waterproof': 0, 'waterworks': 0, 'watery': 1, 'wave': 0, 'waver': 1, 'wavering': 0, 'waves': 0, 'wavy': 0, 'wax': 0, 'waxy': 0, 'ways': 0, 'wayward': 0, 'weakened': 1, 'weakly': 1, 'weakness': 1, 'wealth': 0, 'wealthy': 0, 'weapon': 0, 'wear': 1, 'wearily': 1, 'weariness': 1, 'wearing': 0, 'weary': 1, 'weather': 0, 'weathered': 0, 'weatherproof': 0, 'weave': 0, 'web': 0, 'wed': 0, 'wedded': 0, 'wedge': 0, 'wee': 0, 'weed': 0, 'weeding': 0, 'weeds': 1, 'weedy': 0, 'week': 0, 'weekly': 0, 'weep': 1, 'weeping': 0, 'weigh': 0, 'weighing': 0, 'weight': 1, 'weightless': 0, 'weights': 0, 'weighty': 0, 'weir': 0, 'weird': 1, 'weirdo': 1, 'welcomed': 0, 'weld': 0, 'welfare': 0, 'wellhead': 0, 'welt': 0, 'wen': 1, 'wench': 1, 'western': 0, 'wet': 0, 'whack': 1, 'whale': 0, 'wham': 0, 'wharf': 0, 'whatsoever': 0, 'wheel': 0, 'wheels': 0, 'whereabouts': 0, 'wherefore': 0, 'wherewith': 0, 'wherewithal': 0, 'whet': 0, 'whiff': 0, 'whilst': 0, 'whim': 1, 'whimper': 0, 'whimsical': 0, 'whimsy': 0, 'whine': 1, 'whip': 1, 'whirl': 0, 'whirlpool': 0, 'whirlwind': 1, 'whisk': 0, 'whisker': 0, 'whisky': 1, 'whisper': 0, 'whispered': 0, 'whistle': 0, 'whit': 0, 'white': 0, 'whiteness': 0, 'whitish': 0, 'whiz': 0, 'wholesome': 0, 'wholly': 0, 'whoop': 0, 'whopping': 0, 'whore': 1, 'wick': 0, 'wicked': 1, 'wickedness': 1, 'wicker': 0, 'wicket': 0, 'wide': 0, 'widely': 0, 'widen': 0, 'widespread': 0, 'widow': 0, 'widower': 0, 'width': 0, 'wield': 0, 'wife': 0, 'wig': 0, 'wight': 0, 'wild': 1, 'wildcat': 1, 'wilderness': 0, 'wildfire': 1, 'willful': 1, 'willingly': 0, 'willingness': 0, 'willow': 0, 'wilted': 0, 'wily': 0, 'wimp': 1, 'wimpy': 1, 'wince': 1, 'winch': 0, 'wind': 0, 'windfall': 0, 'winding': 0, 'windmill': 0, 'window': 0, 'windy': 0, 'wine': 0, 'wing': 0, 'winged': 0, 'wink': 0, 'winner': 0, 'winning': 0, 'winnings': 0, 'winter': 0, 'wintry': 0, 'wipe': 0, 'wire': 0, 'wireless': 0, 'wis': 0, 'wisdom': 0, 'wise': 0, 'wishful': 0, 'wistful': 0, 'wit': 0, 'witch': 1, 'witchcraft': 1, 'withal': 0, 'withdraw': 1, 'withdrawal': 0, 'wither': 1, 'withered': 1, 'withstand': 0, 'witness': 0, 'wits': 0, 'witty': 0, 'wizard': 0, 'woe': 1, 'woeful': 1, 'woefully': 1, 'woman': 0, 'womanhood': 0, 'womanly': 0, 'womb': 0, 'wonderful': 0, 'wonderfully': 0, 'wondrous': 0, 'wont': 0, 'woo': 0, 'wood': 0, 'woodcut': 0, 'wooden': 0, 'woodlands': 0, 'woody': 0, 'wooing': 0, 'wool': 0, 'woolly': 0, 'wop': 0, 'word': 0, 'wording': 0, 'words': 1, 'wordy': 0, 'work': 0, 'workbook': 0, 'worker': 0, 'working': 0, 'workman': 0, 'workmanship': 0, 'workplace': 0, 'works': 0, 'workshop': 0, 'world': 0, 'worldly': 0, 'worldwide': 0, 'worm': 1, 'worn': 1, 'worried': 1, 'worry': 1, 'worrying': 1, 'worse': 1, 'worsening': 1, 'worship': 0, 'worth': 0, 'worthless': 1, 'worthy': 0, 'wot': 0, 'wound': 1, 'wrangler': 0, 'wrangling': 1, 'wrap': 0, 'wrapper': 0, 'wrapping': 0, 'wrath': 1, 'wreak': 1, 'wreath': 0, 'wreck': 1, 'wrecked': 1, 'wrench': 1, 'wrest': 0, 'wrestle': 0, 'wrestler': 0, 'wrestling': 1, 'wretch': 1, 'wretched': 1, 'wright': 0, 'wring': 0, 'wrinkle': 0, 'wrinkled': 0, 'wrist': 0, 'wristband': 0, 'wristwatch': 0, 'writ': 0, 'write': 0, 'writer': 0, 'writing': 0, 'written': 0, 'wrong': 1, 'wrongdoing': 1, 'wrongful': 1, 'wrongly': 1, 'wrought': 1, 'wry': 1, 'xenophobia': 1, 'xerox': 0, 'yacht': 0, 'yachting': 0, 'yak': 0, 'yam': 0, 'yank': 0, 'yard': 0, 'yarn': 0, 'yaw': 0, 'yawn': 1, 'yawning': 1, 'yea': 0, 'year': 0, 'yearbook': 0, 'yearling': 0, 'yearly': 0, 'yearn': 0, 'yearning': 1, 'years': 0, 'yeast': 0, 'yell': 1, 'yellow': 0, 'yellows': 1, 'yelp': 1, 'yeoman': 0, 'yesterday': 0, 'yesteryear': 0, 'yew': 0, 'yield': 0, 'yielding': 0, 'yogi': 0, 'yoke': 0, 'yolk': 0, 'yon': 0, 'yonder': 0, 'young': 0, 'younger': 0, 'youth': 0, 'zany': 0, 'zap': 0, 'zeal': 0, 'zealot': 0, 'zealous': 0, 'zebra': 0, 'zenith': 0, 'zephyr': 0, 'zeppelin': 0, 'zest': 0, 'zip': 1, 'zodiac': 0, 'zone': 0, 'zoo': 0, 'zoological': 0, 'zoology': 0, 'zoom': 0}
#For each record
#For each word in record
#Get the word score (score is a number if the word is in Lexicon, 0 if not)
#Add all the scores and find the ploarity
negativenrc = []
strength =[]
for record in corpus:
#print("record", record)
score = 0
words = record.replace("'","").lower().split()
for word in words:
#print("word", word)
if word in (lexicons):
score = score + lexicons[word]
#print("score",score)
strength.append(score)
#print('strength',strength)
if (score > 0):
negativenrc.append('1')
else:
negativenrc.append('0')
#else:
# prediction.append('neutral')
print(negativenrc)
#print(prediction)
['1', '1', '1', '0', '1', '0', '1', '1', '1', '1', '0', '1', '1', '1', '1', '1', '1', '1', '1', '1', '0', '1', '0', '1', '0', '0', '0', '0', '0', '0', '0', '1', '0', '1', '1', '0', '0', '1', '0', '1', '0', '0', '1', '1', '1', '1', '0', '1', '1', '1', '0', '1', '0', '1', '1', '1', '0', '0', '1', '0', '1', '1', '1', '1', '0', '0', '0', '0', '1', '1', '1', '1', '1', '0', '1', '1', '1', '1', '0', '1', '1', '1', '1', '1', '1', '0', '1', '1', '1', '1', '1', '0', '1', '1', '1', '1', '0', '1', '0', '1', '1', '1', '0', '1', '1', '1', '1', '1', '0', '1', '1', '0', '1', '1', '1', '1', '0', '1', '1', '1', '1', '1', '1', '1', '1', '0', '0', '1', '1', '1', '1', '0', '1', '1', '1', '1', '0', '0', '1', '1', '0', '1', '1', '1', '1', '1', '1', '1', '1', '0', '1', '1', '0', '1', '1', '1', '1', '0', '1', '1', '0', '0', '1', '1', '1', '0', '1', '1', '1', '0', '1', '0', '0', '1', '1', '0', '1', '1', '1', '0', '1', '1', '0', '1', '1', '0', '0', '1', '1', '0', '1', '1', '1', '1', '1', '0', '1', '1', '1', '1', '1', '0', '1', '0', '0', '1', '0', '1', '1', '1', '1', '1', '0', '1', '0', '1', '0', '1', '0', '0', '1', '1', '1', '1', '0', '0', '1', '0', '0', '1', '1', '0', '0', '0', '0', '1', '0', '1', '0', '1', '1', '0', '1', '0', '1', '0', '1', '1', '0', '1', '0', '1', '0', '1', '1', '1', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '1', '1', '0', '1', '1', '1', '0', '1', '1', '1', '1', '1', '1', '0', '1', '1', '0', '1', '0', '0', '0', '1', '0', '1', '0', '1', '1', '1', '0', '1', '1', '0', '0', '1', '1', '1', '1', '0', '0', '1', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '1', '0', '0', '1', '0', '1', '0', '1', '1', '1', '0', '0', '0', '1', '1', '1', '0', '1', '0', '0', '1', '0', '1', '0', '0', '0', '0', '0', '0', '1', '1', '0', '1', '0', '0', '0', '1', '1', '1', '1', '1', '0', '0', '1', '1', '0', '1', '1', '0', '1', '1', '1', '0', '0', '0', '0', '1', '1', '0', '1', '1', '1', '0', '1', '1', '1', '0', '1', '1', '1', '1', '1', '1', '1', '1', '1', '0', '1', '1', '0', 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df_new['negativenrc']= negativenrc
df_new.head()
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | tokenized_docs_no_stopwords | preprocessed_docs | word_final | strength_affin | prediction_affin | positivenrc | negativenrc | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | case id worst poor customer service giving res... | -2 | negative | 1 | 1 |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | ['please', 'dont', 'install', 'this', 'app', '... | ['please', 'dont', 'install', 'app', 'people',... | ['please', 'dont', 'install', 'app', 'people',... | please dont install app people stole informati... | -3 | negative | 1 | 1 |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... | ['dont', 'waste', 'your', 'time', 'and', 'mone... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | dont waste time money woohoo payment successfu... | 9 | positive | 1 | 1 |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | worst customer supportthey wont pick call wont... | -5 | negative | 1 | 0 |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... | ['was', 'a', 'happy', 'customer', 'till', 'i',... | ['happy', 'customer', 'till', 'faced', 'error'... | ['happy', 'customer', 'till', 'faced', 'error'... | happy customer till faced error guess even don... | 0 | neutral | 1 | 1 |
#Read the lexicon file
lex_file = open("D:\\11 Project\\Project\\NRC_file - Anger.csv")
lexicons = {}
records = lex_file.readlines()
for record in records:
#print(record) # line contains newline charecter
#print(record.rstrip('\n').split(",")) - to remove new line charecter
lexicons[record.rstrip('\n').split(",")[0]] = int(record.rstrip('\n').split(",")[1])
print(lexicons)
{'aback': 0, 'abacus': 0, 'abandon': 0, 'abandoned': 1, 'abandonment': 1, 'abate': 0, 'abatement': 0, 'abba': 0, 'abbot': 0, 'abbreviate': 0, 'abbreviation': 0, 'abdomen': 0, 'abdominal': 0, 'abduction': 0, 'aberrant': 0, 'aberration': 0, 'abeyance': 0, 'abhor': 1, 'abhorrent': 1, 'abide': 0, 'ability': 0, 'abject': 0, 'ablation': 0, 'ablaze': 0, 'abnormal': 0, 'aboard': 0, 'abode': 0, 'abolish': 1, 'abolition': 0, 'abominable': 0, 'abomination': 1, 'aboriginal': 0, 'abort': 0, 'abortion': 0, 'abortive': 0, 'abound': 0, 'abovementioned': 0, 'abrasion': 0, 'abroad': 0, 'abrogate': 0, 'abrupt': 0, 'abruptly': 0, 'abscess': 0, 'absence': 0, 'absent': 0, 'absentee': 0, 'absenteeism': 0, 'absinthe': 0, 'absolute': 0, 'absolution': 0, 'absorbed': 0, 'absorbent': 0, 'absorbing': 0, 'absorption': 0, 'abstain': 0, 'abstention': 0, 'abstinence': 0, 'abstract': 0, 'abstraction': 0, 'absurd': 0, 'absurdity': 0, 'abundance': 0, 'abundant': 0, 'abuse': 1, 'abutment': 0, 'aby': 0, 'abysmal': 0, 'abyss': 0, 'academic': 0, 'academy': 0, 'accede': 0, 'accelerate': 0, 'acceleration': 0, 'accent': 0, 'accentuate': 0, 'accept': 0, 'acceptable': 0, 'acceptance': 0, 'access': 0, 'accessible': 0, 'accession': 0, 'accessory': 0, 'accident': 0, 'accidental': 0, 'accidentally': 0, 'accolade': 0, 'accommodate': 0, 'accommodation': 0, 'accompaniment': 0, 'accompany': 0, 'accompanying': 0, 'accomplice': 0, 'accomplish': 0, 'accomplished': 0, 'accomplishment': 0, 'accord': 0, 'accordance': 0, 'accordion': 0, 'account': 0, 'accountability': 0, 'accountable': 0, 'accountant': 0, 'accounting': 0, 'accounts': 0, 'accredited': 0, 'accretion': 0, 'accrue': 0, 'accueil': 0, 'accumulate': 0, 'accumulation': 0, 'accuracy': 0, 'accurate': 0, 'accursed': 1, 'accusation': 1, 'accusative': 0, 'accused': 1, 'accuser': 1, 'accusing': 1, 'accustomed': 0, 'ace': 0, 'acetic': 0, 'ache': 0, 'achieve': 0, 'achievement': 0, 'aching': 0, 'acid': 0, 'acidity': 0, 'acknowledge': 0, 'acknowledged': 0, 'acknowledgment': 0, 'acme': 0, 'acoustic': 0, 'acoustics': 0, 'acquaint': 0, 'acquaintance': 0, 'acquainted': 0, 'acquiescence': 0, 'acquire': 0, 'acquiring': 0, 'acquisition': 0, 'acquisitions': 0, 'acreage': 0, 'acres': 0, 'acrobat': 0, 'act': 0, 'acting': 0, 'action': 0, 'actionable': 1, 'active': 0, 'activity': 0, 'actor': 0, 'actual': 0, 'actuality': 0, 'actuary': 0, 'acuity': 0, 'acumen': 0, 'acupuncture': 0, 'acutely': 0, 'adage': 0, 'adamant': 0, 'adapt': 0, 'adaptable': 0, 'add': 0, 'added': 0, 'addendum': 0, 'adder': 1, 'addiction': 0, 'addition': 0, 'additional': 0, 'additive': 0, 'address': 0, 'addressee': 0, 'addresses': 0, 'adept': 0, 'adequacy': 0, 'adequate': 0, 'adhere': 0, 'adherence': 0, 'adherent': 0, 'adhering': 0, 'adhesion': 0, 'adhesive': 0, 'adieu': 0, 'adipose': 0, 'adjacency': 0, 'adjacent': 0, 'adjective': 0, 'adjoining': 0, 'adjourn': 0, 'adjournment': 0, 'adjudicate': 0, 'adjudication': 0, 'adjunct': 0, 'adjust': 0, 'adjustment': 0, 'adjuvant': 0, 'administer': 0, 'administration': 0, 'administrative': 0, 'admirable': 0, 'admiral': 0, 'admiralty': 0, 'admiration': 0, 'admire': 0, 'admirer': 0, 'admissibility': 0, 'admissible': 0, 'admission': 0, 'admit': 0, 'admittance': 0, 'admitted': 0, 'admitting': 0, 'admixture': 0, 'admonition': 0, 'ado': 0, 'adobe': 0, 'adolescence': 0, 'adolescent': 0, 'adopt': 0, 'adoption': 0, 'adorable': 0, 'adoration': 0, 'adore': 0, 'adorn': 0, 'adornment': 0, 'adrift': 0, 'adult': 0, 'adulterated': 0, 'adultery': 0, 'advance': 0, 'advanced': 0, 'advancement': 0, 'advancing': 0, 'advantage': 0, 'advantageous': 0, 'advent': 0, 'adventure': 0, 'adventurer': 0, 'adventurous': 0, 'adversary': 1, 'adverse': 1, 'adversity': 1, 'advertise': 0, 'advertisement': 0, 'advice': 0, 'advisable': 0, 'advise': 0, 'advised': 0, 'advisement': 0, 'adviser': 0, 'advocacy': 1, 'advocate': 0, 'aegis': 0, 'aeration': 0, 'aerial': 0, 'aerodrome': 0, 'aerodynamics': 0, 'aeronautics': 0, 'aeroplane': 0, 'aesthetic': 0, 'aesthetics': 0, 'aetiology': 0, 'afar': 0, 'affable': 0, 'affair': 0, 'affecting': 0, 'affection': 0, 'affections': 0, 'affiche': 0, 'affidavit': 0, 'affiliated': 0, 'affiliation': 0, 'affinity': 0, 'affirm': 0, 'affirmation': 0, 'affirmative': 0, 'affirmatively': 0, 'affix': 0, 'afflict': 0, 'afflicted': 0, 'affliction': 0, 'affluence': 0, 'affluent': 0, 'afford': 0, 'affront': 1, 'afield': 0, 'afore': 0, 'aforementioned': 0, 'aforesaid': 0, 'afraid': 0, 'afresh': 0, 'aft': 0, 'aftermath': 1, 'afternoon': 0, 'aftertaste': 0, 'afterthought': 0, 'aga': 0, 'agate': 0, 'age': 0, 'aged': 0, 'agency': 0, 'agent': 0, 'agglomeration': 0, 'aggravated': 1, 'aggravating': 1, 'aggravation': 1, 'aggregate': 0, 'aggregation': 0, 'aggression': 1, 'aggressive': 1, 'aggressor': 1, 'aghast': 0, 'agile': 0, 'agility': 0, 'agitated': 1, 'agitation': 1, 'agnostic': 0, 'ago': 0, 'agonizing': 0, 'agony': 1, 'agree': 0, 'agreeable': 0, 'agreed': 0, 'agreeing': 0, 'agreement': 0, 'agricultural': 0, 'agriculture': 0, 'aground': 0, 'agua': 0, 'ahead': 0, 'aid': 0, 'aiding': 0, 'ail': 0, 'ailing': 0, 'ailment': 0, 'aim': 0, 'aimless': 0, 'air': 0, 'airbag': 0, 'airlift': 0, 'airline': 0, 'airman': 0, 'airplane': 0, 'airport': 0, 'airs': 0, 'airship': 0, 'aisle': 0, 'ait': 0, 'ajar': 0, 'akin': 0, 'alabaster': 0, 'alarm': 0, 'alarming': 0, 'alb': 0, 'album': 0, 'alchemy': 0, 'alcohol': 0, 'alcoholism': 1, 'alcove': 0, 'alert': 0, 'alertness': 0, 'alerts': 0, 'alfalfa': 0, 'algebra': 0, 'algebraic': 0, 'algorithm': 0, 'alibi': 0, 'alien': 0, 'alienate': 1, 'alienated': 0, 'alienation': 1, 'alight': 0, 'aligned': 0, 'alignment': 0, 'alike': 0, 'alimentation': 0, 'alimony': 0, 'aliquot': 0, 'alive': 0, 'alkali': 0, 'alkaloids': 0, 'allay': 0, 'allegation': 1, 'allege': 0, 'alleged': 0, 'allegiance': 0, 'allegorical': 0, 'allegory': 0, 'allegro': 0, 'alleviate': 0, 'alleviation': 0, 'alley': 0, 'alliance': 0, 'allied': 0, 'alligator': 0, 'allocate': 0, 'allocation': 0, 'allot': 0, 'allotment': 0, 'allowable': 0, 'allowance': 0, 'allowed': 0, 'alloy': 0, 'allure': 0, 'alluring': 0, 'allusion': 0, 'alluvial': 0, 'ally': 0, 'almanac': 0, 'almighty': 0, 'aloft': 0, 'aloha': 0, 'alongside': 0, 'aloof': 0, 'aloud': 0, 'alphabet': 0, 'alphabetical': 0, 'altar': 0, 'alter': 0, 'alteration': 0, 'altercation': 1, 'altered': 0, 'alternate': 0, 'alternative': 0, 'altitude': 0, 'alto': 0, 'altogether': 0, 'alumnus': 0, 'alveolar': 0, 'amalgam': 0, 'amalgamation': 0, 'amass': 0, 'amateur': 0, 'amaze': 0, 'amazement': 0, 'amazingly': 0, 'ambassador': 0, 'amber': 0, 'ambient': 0, 'ambiguity': 0, 'ambiguous': 0, 'ambit': 0, 'ambition': 0, 'ambitious': 0, 'ambulance': 0, 'ambush': 1, 'ameliorate': 0, 'amen': 0, 'amenable': 0, 'amend': 0, 'amendment': 0, 'amends': 0, 'amenity': 0, 'amethyst': 0, 'amiable': 0, 'amicable': 0, 'amid': 0, 'amidst': 0, 'ammonia': 0, 'ammunition': 0, 'amnesia': 0, 'amnesty': 0, 'amorphous': 0, 'amortization': 0, 'amount': 0, 'amour': 0, 'ampersand': 0, 'amphetamines': 0, 'amphibian': 0, 'amphibious': 0, 'amphitheater': 0, 'amplification': 0, 'amplify': 0, 'amplitude': 0, 'amply': 0, 'amputation': 0, 'amulet': 0, 'amuse': 0, 'amused': 0, 'amusement': 0, 'amusing': 0, 'ana': 0, 'anaconda': 0, 'anaesthesia': 0, 'anaesthetic': 0, 'anal': 0, 'analgesic': 0, 'analogous': 0, 'analogue': 0, 'analogy': 0, 'analysis': 0, 'analyst': 0, 'analytic': 0, 'analyze': 0, 'analyzer': 0, 'anarchism': 1, 'anarchist': 1, 'anarchy': 1, 'anastomosis': 0, 'anathema': 1, 'anatomic': 0, 'anatomy': 0, 'ancestor': 0, 'ancestral': 0, 'ancestry': 0, 'anchor': 0, 'anchorage': 0, 'ancient': 0, 'ancillary': 0, 'androgen': 0, 'anemone': 0, 'anew': 0, 'angel': 0, 'angelic': 0, 'anger': 1, 'angina': 0, 'angiography': 0, 'angle': 0, 'angling': 0, 'angry': 1, 'anguish': 1, 'angular': 0, 'anhydrous': 0, 'animal': 0, 'animate': 0, 'animated': 0, 'animation': 0, 'animosity': 1, 'animus': 1, 'ankle': 0, 'annals': 0, 'annex': 0, 'annexation': 0, 'annexe': 0, 'annihilate': 1, 'annihilated': 1, 'annihilation': 1, 'annotate': 0, 'annotation': 0, 'announce': 0, 'announcement': 0, 'annoy': 1, 'annoyance': 1, 'annoying': 1, 'annuity': 0, 'annul': 0, 'annular': 0, 'annulment': 0, 'annulus': 0, 'anointing': 0, 'anomalous': 0, 'anomaly': 0, 'anon': 0, 'anonymous': 0, 'answer': 0, 'answerable': 0, 'answering': 0, 'ant': 0, 'antagonism': 1, 'antagonist': 1, 'antagonistic': 1, 'ante': 0, 'antecedent': 0, 'antelope': 0, 'antenna': 0, 'anterior': 0, 'anthem': 0, 'anthology': 0, 'anthrax': 0, 'anthropology': 0, 'antibiotic': 0, 'antibiotics': 0, 'antichrist': 1, 'anticipation': 0, 'anticipatory': 0, 'antidote': 0, 'antifungal': 0, 'antimony': 0, 'antipathy': 1, 'antiquarian': 0, 'antiquated': 0, 'antique': 0, 'antiquity': 0, 'antiseptic': 0, 'antisocial': 1, 'antithesis': 1, 'antithetical': 0, 'antiviral': 0, 'antler': 0, 'anvil': 0, 'anxiety': 1, 'anxious': 0, 'aorta': 0, 'apace': 0, 'apache': 0, 'apartment': 0, 'apathetic': 0, 'apathy': 0, 'ape': 0, 'aperture': 0, 'apex': 0, 'aphid': 0, 'apiece': 0, 'aplomb': 0, 'apocalyptic': 0, 'apologetic': 0, 'apologist': 0, 'apologize': 0, 'apology': 0, 'apostasy': 0, 'apostate': 0, 'apostle': 0, 'apostolic': 0, 'apostrophe': 0, 'appalling': 0, 'apparatus': 0, 'apparel': 0, 'apparently': 0, 'apparition': 0, 'appeal': 0, 'appearance': 0, 'appease': 0, 'appellant': 0, 'append': 0, 'appendage': 0, 'appendicitis': 0, 'appendix': 0, 'appetite': 0, 'appetizer': 0, 'applause': 0, 'apple': 0, 'appliance': 0, 'appliances': 0, 'applicability': 0, 'applicable': 0, 'applicant': 0, 'application': 0, 'apply': 0, 'appoint': 0, 'appointment': 0, 'appointments': 0, 'apportion': 0, 'apportionment': 0, 'appraise': 0, 'appreciable': 0, 'appreciation': 0, 'apprehend': 0, 'apprehension': 0, 'apprehensive': 0, 'apprentice': 0, 'apprenticeship': 0, 'approach': 0, 'approaching': 0, 'approbation': 0, 'appropriation': 0, 'approval': 0, 'approve': 0, 'approving': 0, 'approximate': 0, 'approximately': 0, 'approximating': 0, 'approximation': 0, 'appurtenances': 0, 'apron': 0, 'apt': 0, 'aptitude': 0, 'aqua': 0, 'aquamarine': 0, 'aquarium': 0, 'aquatic': 0, 'aqueduct': 0, 'aqueous': 0, 'arable': 0, 'arbiter': 0, 'arbitrate': 0, 'arbitration': 0, 'arbitrator': 0, 'arbor': 0, 'arc': 0, 'arcade': 0, 'arch': 0, 'archaeological': 0, 'archaeologist': 0, 'archaeology': 0, 'archaic': 0, 'archbishop': 0, 'arched': 0, 'archer': 0, 'archery': 0, 'archetype': 0, 'archipelago': 0, 'architect': 0, 'architecture': 0, 'archive': 0, 'arctic': 0, 'ardent': 0, 'ardor': 0, 'arduous': 0, 'area': 0, 'arena': 0, 'areola': 0, 'argent': 0, 'argue': 1, 'argument': 1, 'argumentation': 1, 'argumentative': 0, 'arguments': 1, 'arid': 0, 'aristocracy': 0, 'aristocrat': 0, 'aristocratic': 0, 'arithmetic': 0, 'ark': 0, 'arm': 0, 'armada': 0, 'armament': 1, 'armaments': 0, 'armature': 0, 'armed': 1, 'armor': 0, 'armored': 0, 'armory': 0, 'arms': 0, 'army': 0, 'aroma': 0, 'arousal': 0, 'arouse': 0, 'arraignment': 1, 'arrange': 0, 'arranged': 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'vanished': 0, 'vanity': 0, 'vanquish': 0, 'vapor': 0, 'vara': 0, 'variable': 0, 'variance': 0, 'variation': 0, 'variations': 0, 'varicella': 0, 'varicose': 0, 'varied': 0, 'variegated': 0, 'variety': 0, 'vary': 0, 'vascular': 0, 'vase': 0, 'vast': 0, 'vat': 0, 'vaudeville': 0, 'vault': 0, 'vaulted': 0, 'vaulting': 0, 'veal': 0, 'vector': 0, 'veer': 0, 'vega': 0, 'vegetable': 0, 'vegetarian': 0, 'vegetarianism': 0, 'vegetation': 0, 'vegetative': 0, 'vehement': 1, 'vehicle': 0, 'veil': 0, 'veiled': 0, 'vein': 0, 'veined': 0, 'vellum': 0, 'velocity': 0, 'velour': 0, 'velvet': 0, 'velvety': 0, 'vena': 0, 'vendetta': 1, 'vendor': 0, 'veneer': 0, 'venerable': 0, 'veneration': 0, 'vengeance': 1, 'vengeful': 1, 'venison': 0, 'venom': 1, 'venomous': 1, 'venous': 0, 'vent': 1, 'ventilation': 0, 'ventilator': 0, 'ventricle': 0, 'ventricular': 0, 'venture': 0, 'venue': 0, 'veracity': 0, 'veranda': 0, 'verbal': 0, 'verbatim': 0, 'verbiage': 0, 'verbose': 0, 'verbosity': 0, 'verdant': 0, 'verdict': 0, 'verge': 0, 'verification': 0, 'verified': 0, 'verify': 0, 'verily': 0, 'veritable': 0, 'vermin': 1, 'vernacular': 0, 'vernal': 0, 'veronica': 0, 'versatile': 0, 'versatility': 0, 'verse': 0, 'version': 0, 'versus': 1, 'vert': 0, 'vertebra': 0, 'vertebral': 0, 'vertex': 0, 'vertical': 0, 'vertically': 0, 'vertigo': 0, 'verve': 0, 'vesicle': 0, 'vesicular': 0, 'vessel': 0, 'vest': 0, 'vested': 0, 'vestibule': 0, 'vestige': 0, 'vet': 0, 'veteran': 0, 'veterinarian': 0, 'veto': 1, 'viability': 0, 'viable': 0, 'viaduct': 0, 'vial': 0, 'vibrate': 0, 'vibration': 0, 'vibratory': 0, 'vicar': 0, 'vicarious': 0, 'vice': 0, 'vicinity': 0, 'vicious': 1, 'victim': 1, 'victimized': 1, 'victor': 0, 'victoria': 0, 'victorious': 0, 'victory': 0, 'videotape': 0, 'vie': 0, 'view': 0, 'vigil': 0, 'vigilance': 0, 'vigilant': 0, 'vignette': 0, 'vigor': 0, 'vigorous': 0, 'viking': 0, 'villa': 0, 'village': 0, 'villager': 0, 'villain': 0, 'villainous': 1, 'vinaigrette': 0, 'vindicate': 1, 'vindicated': 0, 'vindication': 0, 'vindictive': 1, 'vinegar': 0, 'vineyard': 0, 'viola': 0, 'violation': 1, 'violence': 1, 'violent': 1, 'violently': 1, 'violet': 0, 'violin': 0, 'violinist': 0, 'viper': 0, 'virgin': 0, 'virginity': 0, 'virology': 0, 'virtual': 0, 'virtually': 0, 'virtue': 0, 'virtuoso': 0, 'virtuous': 0, 'virulence': 1, 'virus': 0, 'visa': 0, 'visage': 0, 'viscosity': 0, 'viscous': 0, 'vise': 0, 'visibility': 0, 'visible': 0, 'visibly': 0, 'vision': 0, 'visionary': 0, 'visit': 0, 'visitation': 0, 'visiting': 0, 'visitor': 0, 'visor': 0, 'vista': 0, 'visual': 0, 'visualize': 0, 'vital': 0, 'vitality': 0, 'vitreous': 0, 'vivacious': 0, 'vivid': 0, 'vixen': 0, 'vocabulary': 0, 'vocal': 0, 'vocalist': 0, 'vocation': 0, 'vogue': 0, 'voice': 0, 'voiceless': 0, 'void': 0, 'volatility': 1, 'volcanic': 0, 'volcano': 0, 'volition': 0, 'volley': 0, 'voltmeter': 0, 'volume': 0, 'voluminous': 0, 'voluntarily': 0, 'voluntary': 0, 'volunteer': 0, 'volunteering': 0, 'volunteers': 0, 'voluptuous': 0, 'vomit': 0, 'vomiting': 0, 'voodoo': 0, 'voracious': 0, 'vortex': 0, 'vote': 1, 'voting': 0, 'votive': 0, 'vouch': 0, 'voucher': 0, 'vow': 0, 'vowel': 0, 'voyage': 0, 'voyager': 0, 'vulgar': 0, 'vulgarity': 1, 'vulnerability': 0, 'vulnerable': 0, 'vulture': 0, 'wad': 0, 'wade': 0, 'wafer': 0, 'waffle': 1, 'wag': 0, 'wager': 0, 'wages': 0, 'wagon': 0, 'wail': 0, 'waist': 0, 'waistcoat': 0, 'wait': 0, 'waiter': 0, 'waiting': 0, 'waive': 0, 'wake': 0, 'walk': 0, 'walker': 0, 'wall': 0, 'wallet': 0, 'wallow': 0, 'walnut': 0, 'waltz': 0, 'wan': 0, 'wand': 0, 'wander': 0, 'wanderer': 0, 'wandering': 0, 'wane': 0, 'waning': 0, 'wanting': 0, 'war': 0, 'warbler': 0, 'ward': 0, 'warden': 1, 'wardrobe': 0, 'ware': 0, 'warehouse': 0, 'warfare': 1, 'warlike': 1, 'warlock': 0, 'warming': 0, 'warn': 0, 'warned': 0, 'warning': 0, 'warp': 1, 'warped': 0, 'warrant': 0, 'warranted': 0, 'warrants': 0, 'warranty': 0, 'warren': 0, 'warrior': 1, 'wart': 0, 'wary': 0, 'wash': 0, 'washing': 0, 'washout': 0, 'wasp': 0, 'waste': 0, 'wasted': 1, 'wasteful': 1, 'wasting': 0, 'watch': 0, 'watchdog': 0, 'watchful': 0, 'watchman': 0, 'water': 0, 'watercourse': 0, 'watered': 0, 'waterproof': 0, 'waterworks': 0, 'watery': 0, 'wave': 0, 'waver': 0, 'wavering': 0, 'waves': 0, 'wavy': 0, 'wax': 0, 'waxy': 0, 'ways': 0, 'wayward': 0, 'weakened': 0, 'weakly': 0, 'weakness': 0, 'wealth': 0, 'wealthy': 0, 'weapon': 0, 'wear': 0, 'wearily': 0, 'weariness': 0, 'wearing': 0, 'weary': 0, 'weather': 0, 'weathered': 0, 'weatherproof': 0, 'weave': 0, 'web': 0, 'wed': 0, 'wedded': 0, 'wedge': 0, 'wee': 0, 'weed': 0, 'weeding': 0, 'weeds': 0, 'weedy': 0, 'week': 0, 'weekly': 0, 'weep': 0, 'weeping': 0, 'weigh': 0, 'weighing': 0, 'weight': 0, 'weightless': 0, 'weights': 0, 'weighty': 0, 'weir': 0, 'weird': 0, 'weirdo': 0, 'welcomed': 0, 'weld': 0, 'welfare': 0, 'wellhead': 0, 'welt': 0, 'wen': 0, 'wench': 1, 'western': 0, 'wet': 0, 'whack': 0, 'whale': 0, 'wham': 0, 'wharf': 0, 'whatsoever': 0, 'wheel': 0, 'wheels': 0, 'whereabouts': 0, 'wherefore': 0, 'wherewith': 0, 'wherewithal': 0, 'whet': 0, 'whiff': 0, 'whilst': 0, 'whim': 0, 'whimper': 0, 'whimsical': 0, 'whimsy': 0, 'whine': 0, 'whip': 1, 'whirl': 0, 'whirlpool': 0, 'whirlwind': 0, 'whisk': 0, 'whisker': 0, 'whisky': 0, 'whisper': 0, 'whispered': 0, 'whistle': 0, 'whit': 0, 'white': 0, 'whiteness': 0, 'whitish': 0, 'whiz': 0, 'wholesome': 0, 'wholly': 0, 'whoop': 0, 'whopping': 0, 'whore': 0, 'wick': 0, 'wicked': 0, 'wickedness': 0, 'wicker': 0, 'wicket': 0, 'wide': 0, 'widely': 0, 'widen': 0, 'widespread': 0, 'widow': 0, 'widower': 0, 'width': 0, 'wield': 0, 'wife': 0, 'wig': 0, 'wight': 0, 'wild': 0, 'wildcat': 0, 'wilderness': 0, 'wildfire': 0, 'willful': 1, 'willingly': 0, 'willingness': 0, 'willow': 0, 'wilted': 0, 'wily': 0, 'wimp': 0, 'wimpy': 1, 'wince': 1, 'winch': 0, 'wind': 0, 'windfall': 0, 'winding': 0, 'windmill': 0, 'window': 0, 'windy': 0, 'wine': 0, 'wing': 0, 'winged': 0, 'wink': 0, 'winner': 0, 'winning': 0, 'winnings': 0, 'winter': 0, 'wintry': 0, 'wipe': 0, 'wire': 0, 'wireless': 1, 'wis': 0, 'wisdom': 0, 'wise': 0, 'wishful': 0, 'wistful': 0, 'wit': 0, 'witch': 1, 'witchcraft': 1, 'withal': 0, 'withdraw': 0, 'withdrawal': 0, 'wither': 0, 'withered': 0, 'withstand': 0, 'witness': 0, 'wits': 0, 'witty': 0, 'wizard': 0, 'woe': 0, 'woeful': 0, 'woefully': 0, 'woman': 0, 'womanhood': 0, 'womanly': 0, 'womb': 0, 'wonderful': 0, 'wonderfully': 0, 'wondrous': 0, 'wont': 0, 'woo': 0, 'wood': 0, 'woodcut': 0, 'wooden': 0, 'woodlands': 0, 'woody': 0, 'wooing': 0, 'wool': 0, 'woolly': 0, 'wop': 1, 'word': 0, 'wording': 0, 'words': 1, 'wordy': 0, 'work': 0, 'workbook': 0, 'worker': 0, 'working': 0, 'workman': 0, 'workmanship': 0, 'workplace': 0, 'works': 0, 'workshop': 0, 'world': 0, 'worldly': 0, 'worldwide': 0, 'worm': 0, 'worn': 0, 'worried': 0, 'worry': 0, 'worrying': 0, 'worse': 0, 'worsening': 0, 'worship': 0, 'worth': 0, 'worthless': 1, 'worthy': 0, 'wot': 0, 'wound': 1, 'wrangler': 0, 'wrangling': 1, 'wrap': 0, 'wrapper': 0, 'wrapping': 0, 'wrath': 1, 'wreak': 1, 'wreath': 0, 'wreck': 1, 'wrecked': 1, 'wrench': 0, 'wrest': 0, 'wrestle': 0, 'wrestler': 0, 'wrestling': 0, 'wretch': 1, 'wretched': 0, 'wright': 0, 'wring': 1, 'wrinkle': 0, 'wrinkled': 0, 'wrist': 0, 'wristband': 0, 'wristwatch': 0, 'writ': 0, 'write': 0, 'writer': 0, 'writing': 0, 'written': 0, 'wrong': 0, 'wrongdoing': 1, 'wrongful': 1, 'wrongly': 1, 'wrought': 0, 'wry': 0, 'xenophobia': 0, 'xerox': 0, 'yacht': 0, 'yachting': 0, 'yak': 0, 'yam': 0, 'yank': 0, 'yard': 0, 'yarn': 0, 'yaw': 0, 'yawn': 0, 'yawning': 0, 'yea': 0, 'year': 0, 'yearbook': 0, 'yearling': 0, 'yearly': 0, 'yearn': 0, 'yearning': 0, 'years': 0, 'yeast': 0, 'yell': 1, 'yellow': 0, 'yellows': 0, 'yelp': 1, 'yeoman': 0, 'yesterday': 0, 'yesteryear': 0, 'yew': 0, 'yield': 0, 'yielding': 0, 'yogi': 0, 'yoke': 0, 'yolk': 0, 'yon': 0, 'yonder': 0, 'young': 0, 'younger': 0, 'youth': 1, 'zany': 0, 'zap': 0, 'zeal': 0, 'zealot': 0, 'zealous': 0, 'zebra': 0, 'zenith': 0, 'zephyr': 0, 'zeppelin': 0, 'zest': 0, 'zip': 0, 'zodiac': 0, 'zone': 0, 'zoo': 0, 'zoological': 0, 'zoology': 0, 'zoom': 0}
#For each record
#For each word in record
#Get the word score (score is a number if the word is in Lexicon, 0 if not)
#Add all the scores and find the ploarity
angernrc = []
strength =[]
for record in corpus:
#print("record", record)
score = 0
words = record.replace("'","").lower().split()
for word in words:
#print("word", word)
if word in (lexicons):
score = score + lexicons[word]
#print("score",score)
strength.append(score)
#print('strength',strength)
if (score > 0):
angernrc.append('1')
else:
angernrc.append('0')
#else:
# prediction.append('neutral')
print(angernrc)
#print(prediction)
['1', '0', '1', '0', '0', '1', '0', '1', '1', '1', '0', '0', '0', '0', '1', '0', '1', '0', '1', '0', '0', '1', '0', '1', '0', '0', '1', '0', '0', '0', '0', '1', '1', '1', '0', '0', '1', '1', '0', '1', '0', '0', '0', '1', '1', '1', '1', '0', '0', '1', '0', '0', '0', '0', '0', '1', '0', '1', '0', '0', '1', '1', '0', '0', '1', '0', '0', '0', '1', '1', '0', '0', '0', '0', '1', '1', '0', '1', '0', '0', '1', '1', '1', '0', '1', '0', '1', '1', '1', '0', '0', '0', '0', '0', '1', '1', '0', '1', '0', '0', '0', '0', '0', '1', '1', '0', '1', '0', '0', '0', '1', '0', '0', '0', '1', '1', '0', '1', '1', '0', '1', '1', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '1', '1', '1', '0', '0', '0', '1', '1', '0', '1', '1', '0', '1', '1', '1', '0', '1', '0', '1', '0', '0', '0', '0', '0', '0', '0', '1', '1', '1', '0', '1', '1', '1', '0', '0', '0', '0', '0', '0', '0', '0', '1', '1', '0', '0', '0', '1', '0', '1', '1', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '1', '1', '0', '1', '1', '1', '1', '0', '1', '0', '1', '0', '0', '1', '0', '0', '1', '0', '0', '0', '0', '1', '0', '0', '0', '1', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '1', '1', '0', '0', '0', '0', '1', '0', '1', '0', '0', '0', '0', '1', '0', '0', '0', '1', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '1', '0', '0', '1', '1', '0', '0', '1', '0', '0', '1', '0', '0', '0', '0', '0', '1', '0', '1', '1', '1', '1', '0', '0', '1', '1', '1', '0', '1', '1', '1', '1', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '1', '0', '1', '1', '0', '0', '0', '1', '1', '1', '0', '0', '0', '1', '1', '1', '0', '1', '0', '0', '1', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '1', '0', '0', '1', '0', '0', '0', '1', '0', '1', '1', '0', '0', '1', '0', '0', '0', '0', '0', '0', '1', '1', '1', '1', '1', '1', '0', '0', '1', '0', '1', '0', '0', '1', '0', '0', '0', '1', '1', '0', '1', '0', '0', '0', '1', '1', '0', '0', '0', '0', '0', '1', '0', '1', '1', '1', '1', '1', '0', '1', '0', '1', '0', '1', '1', '1', '1', '1', '1', '1', '1', '0', '0', '1', '0', '1', '1', '0', '1', '0', '0', '0', '0', '0', '1', '1', '0', '0', '0', '0', '1', '1', '1', '0', '0', '1', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '1', '1', '1', '0', '1', '0', '1', '1', '1', '1', '1', '0', '1', '1', '1', '0', '1', '0', '0', '0', '0', '0', '1', '0', '1', '0', '1', '0', '0', '0', '0', '1', '1', '0', '0', '1', '0', '0', '0', '0', '1', '1', '0', '0', '0', '1', '0', '1', '0', '1', '0', '1', '0', '1', '0', '0', '0', '0', '0', '1', '0', '1', '1', '1', '1', '1', '1', '1', '0', '0', '1', '1', '0', '1', '0', '0', '1', '1', '0', '1', '1', '0', '0', '0', '0', '0', '1', '1', '1', '0', '0', '1', '0', '0', '0', '0', '1', '1', '0', '1', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '1', '0', '1', '0', '0', '0', '1', '0', '0', '0', '0', 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df_new['angernrc']= angernrc
df_new.head()
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | tokenized_docs_no_stopwords | preprocessed_docs | word_final | strength_affin | prediction_affin | positivenrc | negativenrc | angernrc | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | case id worst poor customer service giving res... | -2 | negative | 1 | 1 | 1 |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | ['please', 'dont', 'install', 'this', 'app', '... | ['please', 'dont', 'install', 'app', 'people',... | ['please', 'dont', 'install', 'app', 'people',... | please dont install app people stole informati... | -3 | negative | 1 | 1 | 0 |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... | ['dont', 'waste', 'your', 'time', 'and', 'mone... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | dont waste time money woohoo payment successfu... | 9 | positive | 1 | 1 | 1 |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | worst customer supportthey wont pick call wont... | -5 | negative | 1 | 0 | 0 |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... | ['was', 'a', 'happy', 'customer', 'till', 'i',... | ['happy', 'customer', 'till', 'faced', 'error'... | ['happy', 'customer', 'till', 'faced', 'error'... | happy customer till faced error guess even don... | 0 | neutral | 1 | 1 | 0 |
#Read the lexicon file
lex_file = open("D:\\11 Project\\Project\\NRC_file - Anticipation.csv")
lexicons = {}
records = lex_file.readlines()
for record in records:
#print(record) # line contains newline charecter
#print(record.rstrip('\n').split(",")) - to remove new line charecter
lexicons[record.rstrip('\n').split(",")[0]] = int(record.rstrip('\n').split(",")[1])
print(lexicons)
{'aback': 0, 'abacus': 0, 'abandon': 0, 'abandoned': 0, 'abandonment': 0, 'abate': 0, 'abatement': 0, 'abba': 0, 'abbot': 0, 'abbreviate': 0, 'abbreviation': 0, 'abdomen': 0, 'abdominal': 0, 'abduction': 0, 'aberrant': 0, 'aberration': 0, 'abeyance': 0, 'abhor': 0, 'abhorrent': 0, 'abide': 0, 'ability': 0, 'abject': 0, 'ablation': 0, 'ablaze': 0, 'abnormal': 0, 'aboard': 0, 'abode': 0, 'abolish': 0, 'abolition': 0, 'abominable': 0, 'abomination': 0, 'aboriginal': 0, 'abort': 0, 'abortion': 0, 'abortive': 0, 'abound': 0, 'abovementioned': 0, 'abrasion': 0, 'abroad': 0, 'abrogate': 0, 'abrupt': 0, 'abruptly': 0, 'abscess': 0, 'absence': 0, 'absent': 0, 'absentee': 0, 'absenteeism': 0, 'absinthe': 0, 'absolute': 0, 'absolution': 0, 'absorbed': 0, 'absorbent': 0, 'absorbing': 0, 'absorption': 0, 'abstain': 0, 'abstention': 0, 'abstinence': 0, 'abstract': 0, 'abstraction': 0, 'absurd': 0, 'absurdity': 0, 'abundance': 1, 'abundant': 0, 'abuse': 0, 'abutment': 0, 'aby': 0, 'abysmal': 0, 'abyss': 0, 'academic': 0, 'academy': 0, 'accede': 0, 'accelerate': 1, 'acceleration': 0, 'accent': 0, 'accentuate': 0, 'accept': 0, 'acceptable': 0, 'acceptance': 0, 'access': 0, 'accessible': 0, 'accession': 0, 'accessory': 0, 'accident': 0, 'accidental': 0, 'accidentally': 0, 'accolade': 1, 'accommodate': 0, 'accommodation': 0, 'accompaniment': 1, 'accompany': 0, 'accompanying': 0, 'accomplice': 0, 'accomplish': 0, 'accomplished': 0, 'accomplishment': 0, 'accord': 0, 'accordance': 0, 'accordion': 0, 'account': 0, 'accountability': 0, 'accountable': 0, 'accountant': 0, 'accounting': 0, 'accounts': 0, 'accredited': 0, 'accretion': 0, 'accrue': 0, 'accueil': 0, 'accumulate': 0, 'accumulation': 0, 'accuracy': 0, 'accurate': 0, 'accursed': 0, 'accusation': 0, 'accusative': 0, 'accused': 0, 'accuser': 0, 'accusing': 0, 'accustomed': 0, 'ace': 0, 'acetic': 0, 'ache': 0, 'achieve': 0, 'achievement': 1, 'aching': 0, 'acid': 0, 'acidity': 0, 'acknowledge': 0, 'acknowledged': 0, 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'aesthetics': 0, 'aetiology': 0, 'afar': 0, 'affable': 0, 'affair': 0, 'affecting': 0, 'affection': 0, 'affections': 0, 'affiche': 0, 'affidavit': 0, 'affiliated': 0, 'affiliation': 0, 'affinity': 0, 'affirm': 0, 'affirmation': 0, 'affirmative': 0, 'affirmatively': 0, 'affix': 0, 'afflict': 0, 'afflicted': 0, 'affliction': 0, 'affluence': 0, 'affluent': 0, 'afford': 0, 'affront': 0, 'afield': 0, 'afore': 0, 'aforementioned': 0, 'aforesaid': 0, 'afraid': 0, 'afresh': 0, 'aft': 0, 'aftermath': 0, 'afternoon': 0, 'aftertaste': 0, 'afterthought': 0, 'aga': 0, 'agate': 0, 'age': 0, 'aged': 0, 'agency': 0, 'agent': 0, 'agglomeration': 0, 'aggravated': 0, 'aggravating': 0, 'aggravation': 0, 'aggregate': 0, 'aggregation': 0, 'aggression': 0, 'aggressive': 0, 'aggressor': 0, 'aghast': 0, 'agile': 0, 'agility': 0, 'agitated': 0, 'agitation': 0, 'agnostic': 0, 'ago': 0, 'agonizing': 0, 'agony': 0, 'agree': 0, 'agreeable': 0, 'agreed': 0, 'agreeing': 0, 'agreement': 0, 'agricultural': 0, 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'amphetamines': 0, 'amphibian': 0, 'amphibious': 0, 'amphitheater': 0, 'amplification': 0, 'amplify': 0, 'amplitude': 0, 'amply': 0, 'amputation': 0, 'amulet': 0, 'amuse': 0, 'amused': 0, 'amusement': 0, 'amusing': 0, 'ana': 0, 'anaconda': 0, 'anaesthesia': 0, 'anaesthetic': 0, 'anal': 0, 'analgesic': 0, 'analogous': 0, 'analogue': 0, 'analogy': 0, 'analysis': 0, 'analyst': 1, 'analytic': 0, 'analyze': 0, 'analyzer': 0, 'anarchism': 0, 'anarchist': 0, 'anarchy': 0, 'anastomosis': 0, 'anathema': 0, 'anatomic': 0, 'anatomy': 0, 'ancestor': 0, 'ancestral': 0, 'ancestry': 0, 'anchor': 0, 'anchorage': 0, 'ancient': 0, 'ancillary': 0, 'androgen': 0, 'anemone': 0, 'anew': 0, 'angel': 1, 'angelic': 0, 'anger': 0, 'angina': 0, 'angiography': 0, 'angle': 0, 'angling': 1, 'angry': 0, 'anguish': 0, 'angular': 0, 'anhydrous': 0, 'animal': 0, 'animate': 0, 'animated': 0, 'animation': 0, 'animosity': 0, 'animus': 0, 'ankle': 0, 'annals': 0, 'annex': 0, 'annexation': 0, 'annexe': 0, 'annihilate': 0, 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'wheels': 0, 'whereabouts': 0, 'wherefore': 0, 'wherewith': 0, 'wherewithal': 0, 'whet': 0, 'whiff': 0, 'whilst': 0, 'whim': 1, 'whimper': 0, 'whimsical': 0, 'whimsy': 0, 'whine': 0, 'whip': 0, 'whirl': 0, 'whirlpool': 0, 'whirlwind': 0, 'whisk': 0, 'whisker': 0, 'whisky': 0, 'whisper': 0, 'whispered': 0, 'whistle': 0, 'whit': 0, 'white': 1, 'whiteness': 0, 'whitish': 0, 'whiz': 0, 'wholesome': 0, 'wholly': 0, 'whoop': 0, 'whopping': 0, 'whore': 0, 'wick': 0, 'wicked': 0, 'wickedness': 0, 'wicker': 0, 'wicket': 0, 'wide': 0, 'widely': 0, 'widen': 0, 'widespread': 0, 'widow': 0, 'widower': 0, 'width': 0, 'wield': 0, 'wife': 0, 'wig': 0, 'wight': 0, 'wild': 0, 'wildcat': 0, 'wilderness': 1, 'wildfire': 0, 'willful': 0, 'willingly': 0, 'willingness': 0, 'willow': 0, 'wilted': 0, 'wily': 0, 'wimp': 0, 'wimpy': 0, 'wince': 0, 'winch': 0, 'wind': 0, 'windfall': 0, 'winding': 0, 'windmill': 0, 'window': 0, 'windy': 0, 'wine': 0, 'wing': 0, 'winged': 0, 'wink': 0, 'winner': 1, 'winning': 1, 'winnings': 1, 'winter': 0, 'wintry': 0, 'wipe': 0, 'wire': 0, 'wireless': 1, 'wis': 0, 'wisdom': 0, 'wise': 0, 'wishful': 1, 'wistful': 0, 'wit': 0, 'witch': 0, 'witchcraft': 0, 'withal': 0, 'withdraw': 0, 'withdrawal': 0, 'wither': 0, 'withered': 0, 'withstand': 1, 'witness': 0, 'wits': 0, 'witty': 0, 'wizard': 1, 'woe': 0, 'woeful': 0, 'woefully': 0, 'woman': 0, 'womanhood': 0, 'womanly': 0, 'womb': 0, 'wonderful': 0, 'wonderfully': 0, 'wondrous': 0, 'wont': 1, 'woo': 0, 'wood': 0, 'woodcut': 0, 'wooden': 0, 'woodlands': 0, 'woody': 0, 'wooing': 0, 'wool': 0, 'woolly': 0, 'wop': 0, 'word': 0, 'wording': 0, 'words': 0, 'wordy': 0, 'work': 0, 'workbook': 0, 'worker': 0, 'working': 0, 'workman': 0, 'workmanship': 0, 'workplace': 0, 'works': 0, 'workshop': 0, 'world': 0, 'worldly': 0, 'worldwide': 0, 'worm': 1, 'worn': 0, 'worried': 0, 'worry': 1, 'worrying': 1, 'worse': 0, 'worsening': 0, 'worship': 1, 'worth': 0, 'worthless': 0, 'worthy': 0, 'wot': 0, 'wound': 0, 'wrangler': 0, 'wrangling': 0, 'wrap': 0, 'wrapper': 0, 'wrapping': 0, 'wrath': 0, 'wreak': 0, 'wreath': 0, 'wreck': 0, 'wrecked': 0, 'wrench': 0, 'wrest': 0, 'wrestle': 0, 'wrestler': 0, 'wrestling': 0, 'wretch': 0, 'wretched': 0, 'wright': 0, 'wring': 0, 'wrinkle': 0, 'wrinkled': 0, 'wrist': 0, 'wristband': 0, 'wristwatch': 0, 'writ': 0, 'write': 0, 'writer': 0, 'writing': 0, 'written': 0, 'wrong': 0, 'wrongdoing': 0, 'wrongful': 0, 'wrongly': 0, 'wrought': 0, 'wry': 0, 'xenophobia': 0, 'xerox': 0, 'yacht': 0, 'yachting': 0, 'yak': 0, 'yam': 0, 'yank': 0, 'yard': 0, 'yarn': 0, 'yaw': 0, 'yawn': 0, 'yawning': 0, 'yea': 0, 'year': 0, 'yearbook': 0, 'yearling': 0, 'yearly': 0, 'yearn': 0, 'yearning': 1, 'years': 0, 'yeast': 0, 'yell': 0, 'yellow': 0, 'yellows': 0, 'yelp': 0, 'yeoman': 0, 'yesterday': 0, 'yesteryear': 0, 'yew': 0, 'yield': 0, 'yielding': 0, 'yogi': 0, 'yoke': 0, 'yolk': 0, 'yon': 0, 'yonder': 0, 'young': 1, 'younger': 0, 'youth': 1, 'zany': 0, 'zap': 0, 'zeal': 1, 'zealot': 0, 'zealous': 0, 'zebra': 0, 'zenith': 0, 'zephyr': 0, 'zeppelin': 0, 'zest': 1, 'zip': 0, 'zodiac': 0, 'zone': 0, 'zoo': 0, 'zoological': 0, 'zoology': 0, 'zoom': 0}
#For each record
#For each word in record
#Get the word score (score is a number if the word is in Lexicon, 0 if not)
#Add all the scores and find the ploarity
anticipationnrc = []
strength =[]
for record in corpus:
#print("record", record)
score = 0
words = record.replace("'","").lower().split()
for word in words:
#print("word", word)
if word in (lexicons):
score = score + lexicons[word]
#print("score",score)
strength.append(score)
#print('strength',strength)
if (score > 0):
anticipationnrc.append('1')
else:
anticipationnrc.append('0')
#else:
# prediction.append('neutral')
print(anticipationnrc)
#print(prediction)
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df_new['anticipationnrc']= anticipationnrc
df_new.head()
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | tokenized_docs_no_stopwords | preprocessed_docs | word_final | strength_affin | prediction_affin | positivenrc | negativenrc | angernrc | anticipationnrc | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | case id worst poor customer service giving res... | -2 | negative | 1 | 1 | 1 | 0 |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | ['please', 'dont', 'install', 'this', 'app', '... | ['please', 'dont', 'install', 'app', 'people',... | ['please', 'dont', 'install', 'app', 'people',... | please dont install app people stole informati... | -3 | negative | 1 | 1 | 0 | 1 |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... | ['dont', 'waste', 'your', 'time', 'and', 'mone... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | dont waste time money woohoo payment successfu... | 9 | positive | 1 | 1 | 1 | 1 |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | worst customer supportthey wont pick call wont... | -5 | negative | 1 | 0 | 0 | 1 |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... | ['was', 'a', 'happy', 'customer', 'till', 'i',... | ['happy', 'customer', 'till', 'faced', 'error'... | ['happy', 'customer', 'till', 'faced', 'error'... | happy customer till faced error guess even don... | 0 | neutral | 1 | 1 | 0 | 1 |
#Read the lexicon file
lex_file = open("D:\\11 Project\\Project\\NRC_file - Disgust.csv")
lexicons = {}
records = lex_file.readlines()
for record in records:
#print(record) # line contains newline charecter
#print(record.rstrip('\n').split(",")) - to remove new line charecter
lexicons[record.rstrip('\n').split(",")[0]] = int(record.rstrip('\n').split(",")[1])
print(lexicons)
{'aback': 0, 'abacus': 0, 'abandon': 0, 'abandoned': 0, 'abandonment': 0, 'abate': 0, 'abatement': 0, 'abba': 0, 'abbot': 0, 'abbreviate': 0, 'abbreviation': 0, 'abdomen': 0, 'abdominal': 0, 'abduction': 0, 'aberrant': 0, 'aberration': 1, 'abeyance': 0, 'abhor': 1, 'abhorrent': 1, 'abide': 0, 'ability': 0, 'abject': 1, 'ablation': 0, 'ablaze': 0, 'abnormal': 1, 'aboard': 0, 'abode': 0, 'abolish': 0, 'abolition': 0, 'abominable': 1, 'abomination': 1, 'aboriginal': 0, 'abort': 0, 'abortion': 1, 'abortive': 0, 'abound': 0, 'abovementioned': 0, 'abrasion': 0, 'abroad': 0, 'abrogate': 0, 'abrupt': 0, 'abruptly': 0, 'abscess': 0, 'absence': 0, 'absent': 0, 'absentee': 0, 'absenteeism': 0, 'absinthe': 0, 'absolute': 0, 'absolution': 0, 'absorbed': 0, 'absorbent': 0, 'absorbing': 0, 'absorption': 0, 'abstain': 0, 'abstention': 0, 'abstinence': 0, 'abstract': 0, 'abstraction': 0, 'absurd': 0, 'absurdity': 0, 'abundance': 1, 'abundant': 0, 'abuse': 1, 'abutment': 0, 'aby': 0, 'abysmal': 0, 'abyss': 0, 'academic': 0, 'academy': 0, 'accede': 0, 'accelerate': 0, 'acceleration': 0, 'accent': 0, 'accentuate': 0, 'accept': 0, 'acceptable': 0, 'acceptance': 0, 'access': 0, 'accessible': 0, 'accession': 0, 'accessory': 0, 'accident': 0, 'accidental': 0, 'accidentally': 0, 'accolade': 0, 'accommodate': 0, 'accommodation': 0, 'accompaniment': 0, 'accompany': 0, 'accompanying': 0, 'accomplice': 0, 'accomplish': 0, 'accomplished': 0, 'accomplishment': 0, 'accord': 0, 'accordance': 0, 'accordion': 0, 'account': 0, 'accountability': 0, 'accountable': 0, 'accountant': 0, 'accounting': 0, 'accounts': 0, 'accredited': 0, 'accretion': 0, 'accrue': 0, 'accueil': 0, 'accumulate': 0, 'accumulation': 0, 'accuracy': 0, 'accurate': 0, 'accursed': 0, 'accusation': 1, 'accusative': 0, 'accused': 0, 'accuser': 0, 'accusing': 0, 'accustomed': 0, 'ace': 0, 'acetic': 0, 'ache': 0, 'achieve': 0, 'achievement': 0, 'aching': 0, 'acid': 0, 'acidity': 0, 'acknowledge': 0, 'acknowledged': 0, 'acknowledgment': 0, 'acme': 0, 'acoustic': 0, 'acoustics': 0, 'acquaint': 0, 'acquaintance': 0, 'acquainted': 0, 'acquiescence': 0, 'acquire': 0, 'acquiring': 0, 'acquisition': 0, 'acquisitions': 0, 'acreage': 0, 'acres': 0, 'acrobat': 0, 'act': 0, 'acting': 0, 'action': 0, 'actionable': 1, 'active': 0, 'activity': 0, 'actor': 0, 'actual': 0, 'actuality': 0, 'actuary': 0, 'acuity': 0, 'acumen': 0, 'acupuncture': 0, 'acutely': 0, 'adage': 0, 'adamant': 0, 'adapt': 0, 'adaptable': 0, 'add': 0, 'added': 0, 'addendum': 0, 'adder': 1, 'addiction': 0, 'addition': 0, 'additional': 0, 'additive': 0, 'address': 0, 'addressee': 0, 'addresses': 0, 'adept': 0, 'adequacy': 0, 'adequate': 0, 'adhere': 0, 'adherence': 0, 'adherent': 0, 'adhering': 0, 'adhesion': 0, 'adhesive': 0, 'adieu': 0, 'adipose': 0, 'adjacency': 0, 'adjacent': 0, 'adjective': 0, 'adjoining': 0, 'adjourn': 0, 'adjournment': 0, 'adjudicate': 0, 'adjudication': 0, 'adjunct': 0, 'adjust': 0, 'adjustment': 0, 'adjuvant': 0, 'administer': 0, 'administration': 0, 'administrative': 0, 'admirable': 0, 'admiral': 0, 'admiralty': 0, 'admiration': 0, 'admire': 0, 'admirer': 0, 'admissibility': 0, 'admissible': 0, 'admission': 0, 'admit': 0, 'admittance': 0, 'admitted': 0, 'admitting': 0, 'admixture': 0, 'admonition': 0, 'ado': 0, 'adobe': 0, 'adolescence': 0, 'adolescent': 0, 'adopt': 0, 'adoption': 0, 'adorable': 0, 'adoration': 0, 'adore': 0, 'adorn': 0, 'adornment': 0, 'adrift': 0, 'adult': 0, 'adulterated': 0, 'adultery': 1, 'advance': 0, 'advanced': 0, 'advancement': 0, 'advancing': 0, 'advantage': 0, 'advantageous': 0, 'advent': 0, 'adventure': 0, 'adventurer': 0, 'adventurous': 0, 'adversary': 0, 'adverse': 1, 'adversity': 0, 'advertise': 0, 'advertisement': 0, 'advice': 0, 'advisable': 0, 'advise': 0, 'advised': 0, 'advisement': 0, 'adviser': 0, 'advocacy': 0, 'advocate': 0, 'aegis': 0, 'aeration': 0, 'aerial': 0, 'aerodrome': 0, 'aerodynamics': 0, 'aeronautics': 0, 'aeroplane': 0, 'aesthetic': 0, 'aesthetics': 0, 'aetiology': 0, 'afar': 0, 'affable': 0, 'affair': 0, 'affecting': 0, 'affection': 0, 'affections': 0, 'affiche': 0, 'affidavit': 0, 'affiliated': 0, 'affiliation': 0, 'affinity': 0, 'affirm': 0, 'affirmation': 0, 'affirmative': 0, 'affirmatively': 0, 'affix': 0, 'afflict': 0, 'afflicted': 0, 'affliction': 1, 'affluence': 0, 'affluent': 0, 'afford': 0, 'affront': 1, 'afield': 0, 'afore': 0, 'aforementioned': 0, 'aforesaid': 0, 'afraid': 0, 'afresh': 0, 'aft': 0, 'aftermath': 1, 'afternoon': 0, 'aftertaste': 0, 'afterthought': 0, 'aga': 0, 'agate': 0, 'age': 0, 'aged': 0, 'agency': 0, 'agent': 0, 'agglomeration': 0, 'aggravated': 0, 'aggravating': 0, 'aggravation': 1, 'aggregate': 0, 'aggregation': 0, 'aggression': 0, 'aggressive': 0, 'aggressor': 0, 'aghast': 1, 'agile': 0, 'agility': 0, 'agitated': 0, 'agitation': 0, 'agnostic': 0, 'ago': 0, 'agonizing': 0, 'agony': 0, 'agree': 0, 'agreeable': 0, 'agreed': 0, 'agreeing': 0, 'agreement': 0, 'agricultural': 0, 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'unattached': 0, 'unattainable': 0, 'unattended': 0, 'unattractive': 1, 'unauthorized': 0, 'unavoidable': 0, 'unaware': 0, 'unbalanced': 0, 'unbearable': 1, 'unbeaten': 0, 'unbelief': 0, 'unbelievable': 0, 'unbiased': 0, 'unborn': 0, 'unbound': 0, 'unbounded': 0, 'unbreakable': 0, 'unbridled': 0, 'unbroken': 0, 'uncanny': 0, 'uncaring': 1, 'uncertain': 1, 'uncertainty': 0, 'unchallenged': 0, 'unchangeable': 0, 'unchanged': 0, 'unclaimed': 0, 'uncle': 0, 'unclean': 1, 'uncomfortable': 0, 'uncommon': 0, 'uncommonly': 0, 'uncompromising': 0, 'unconcerned': 0, 'unconfirmed': 0, 'unconnected': 0, 'unconscionable': 1, 'unconscious': 0, 'unconsciousness': 0, 'unconstitutional': 0, 'unconstrained': 0, 'uncontested': 0, 'uncontrollable': 0, 'uncontrolled': 0, 'unconventional': 0, 'unconvinced': 0, 'uncooked': 0, 'uncorrelated': 0, 'uncover': 0, 'uncritical': 0, 'uncut': 0, 'undecided': 0, 'undefined': 0, 'undeniable': 0, 'undercover': 0, 'undercurrent': 0, 'underestimate': 0, 'undergo': 0, 'undergraduate': 0, 'underground': 0, 'underlie': 0, 'underline': 0, 'undermined': 0, 'underneath': 0, 'underpaid': 0, 'underpants': 0, 'underscore': 0, 'undersized': 0, 'understanding': 0, 'understood': 0, 'undertake': 0, 'undertaker': 0, 'undertaking': 0, 'underwood': 0, 'underwrite': 0, 'underwriter': 0, 'undeserved': 0, 'undesirable': 1, 'undesired': 0, 'undeveloped': 0, 'undirected': 0, 'undisclosed': 0, 'undiscovered': 0, 'undisputed': 0, 'undisturbed': 0, 'undivided': 0, 'undo': 0, 'undoing': 0, 'undoubted': 1, 'undress': 0, 'undressed': 0, 'undue': 0, 'undying': 0, 'unearned': 0, 'unearth': 0, 'uneasiness': 0, 'uneasy': 1, 'uneducated': 0, 'unemployed': 0, 'unencumbered': 0, 'unending': 0, 'unequal': 1, 'unequalled': 0, 'unequivocal': 0, 'unequivocally': 0, 'uneven': 0, 'uneventful': 0, 'unexpected': 0, 'unexpectedly': 0, 'unexplained': 0, 'unexplored': 0, 'unfailing': 0, 'unfair': 1, 'unfairness': 0, 'unfaithful': 1, 'unfamiliar': 0, 'unfavorable': 1, 'unfettered': 0, 'unfinished': 0, 'unflinching': 0, 'unfold': 0, 'unforeseen': 0, 'unforgiving': 0, 'unfortunate': 0, 'unfriendly': 1, 'unfulfilled': 0, 'unfurnished': 0, 'ungodly': 0, 'ungrateful': 1, 'unguarded': 0, 'unhappiness': 0, 'unhappy': 1, 'unharmed': 0, 'unhealthy': 1, 'unhindered': 0, 'unholy': 0, 'unicorn': 0, 'unification': 0, 'uniform': 0, 'uniformity': 0, 'uniformly': 0, 'unimaginable': 0, 'unimportant': 0, 'unimpressed': 0, 'unimproved': 0, 'uninfected': 0, 'uninformed': 0, 'uninhabited': 0, 'uninitiated': 0, 'uninspired': 0, 'unintelligible': 0, 'unintended': 0, 'unintentional': 0, 'unintentionally': 0, 'uninterested': 0, 'uninteresting': 0, 'uninterrupted': 0, 'uninvited': 0, 'union': 0, 'unique': 0, 'unison': 0, 'unit': 0, 'unitary': 0, 'unite': 0, 'united': 0, 'unity': 0, 'universal': 0, 'universality': 0, 'universe': 0, 'university': 0, 'unjust': 0, 'unjustifiable': 1, 'unjustified': 0, 'unkind': 1, 'unknowable': 0, 'unknown': 0, 'unlawful': 1, 'unleash': 0, 'unlicensed': 0, 'unlike': 0, 'unlimited': 0, 'unload': 0, 'unloaded': 0, 'unlock': 0, 'unlucky': 1, 'unmanageable': 1, 'unmarked': 0, 'unmarried': 0, 'unmask': 0, 'unmatched': 0, 'unmistakable': 0, 'unmitigated': 0, 'unmoved': 0, 'unnamed': 0, 'unnatural': 1, 'unnecessary': 0, 'unneeded': 0, 'unnoticed': 0, 'unnumbered': 0, 'unobserved': 0, 'unobstructed': 0, 'unobtrusive': 0, 'unoccupied': 0, 'unofficial': 0, 'unopened': 0, 'unopposed': 0, 'unordered': 0, 'unorganized': 0, 'unorthodox': 0, 'unpack': 0, 'unpaid': 0, 'unpleasant': 1, 'unpopular': 1, 'unprecedented': 0, 'unpredictable': 0, 'unprepared': 0, 'unpretentious': 0, 'unproductive': 0, 'unprofitable': 0, 'unprotected': 0, 'unproven': 0, 'unpublished': 0, 'unquestionable': 0, 'unquestionably': 0, 'unquestioned': 0, 'unread': 0, 'unreal': 0, 'unrealistic': 0, 'unrecorded': 0, 'unregistered': 0, 'unregulated': 0, 'unrelated': 0, 'unrelenting': 0, 'unreliable': 0, 'unrepentant': 0, 'unrequited': 0, 'unresolved': 0, 'unrest': 0, 'unrestrained': 0, 'unrestricted': 0, 'unruly': 1, 'unsafe': 0, 'unsatisfactory': 1, 'unsatisfied': 1, 'unsavory': 0, 'unscathed': 0, 'unscientific': 0, 'unscrupulous': 0, 'unseat': 0, 'unseen': 0, 'unselfish': 0, 'unsettled': 1, 'unsightly': 1, 'unsophisticated': 0, 'unspeakable': 0, 'unspecified': 0, 'unstable': 0, 'unsteady': 0, 'unsuccessful': 0, 'unsuitable': 0, 'unsung': 0, 'unsupported': 0, 'unsurpassed': 0, 'unsuspecting': 0, 'unsustainable': 0, 'unsweetened': 0, 'unsympathetic': 0, 'untamed': 0, 'untenable': 0, 'untested': 0, 'unthinkable': 1, 'untidy': 1, 'untie': 0, 'untimely': 0, 'untitled': 0, 'untold': 0, 'untouched': 0, 'untoward': 1, 'untrained': 0, 'untranslated': 0, 'untrue': 0, 'untrustworthy': 0, 'unused': 0, 'unusual': 0, 'unusually': 0, 'unveil': 0, 'unveiling': 0, 'unverified': 0, 'unwarranted': 0, 'unwary': 0, 'unwashed': 1, 'unwavering': 0, 'unwelcome': 0, 'unwell': 0, 'unwilling': 0, 'unwillingly': 0, 'unwillingness': 0, 'unwind': 0, 'unwise': 0, 'unwitting': 0, 'unwittingly': 0, 'unworthy': 1, 'unwritten': 0, 'unyielding': 0, 'upheaval': 0, 'uphill': 0, 'upholstery': 0, 'upland': 0, 'uplands': 0, 'uplift': 0, 'upper': 0, 'upright': 0, 'uprising': 0, 'uproar': 0, 'upset': 0, 'upshot': 0, 'upstairs': 0, 'upstart': 0, 'upwards': 0, 'uranium': 0, 'urban': 0, 'urchin': 0, 'urge': 0, 'urgency': 0, 'urgent': 0, 'urinalysis': 0, 'urn': 0, 'usage': 0, 'usefully': 0, 'usefulness': 0, 'useless': 0, 'usher': 0, 'usual': 0, 'usurp': 0, 'usurped': 0, 'usury': 0, 'utensil': 0, 'utilitarian': 0, 'utility': 0, 'utilization': 0, 'utilize': 0, 'utmost': 0, 'utopian': 0, 'utterance': 0, 'utterly': 0, 'vacancy': 0, 'vacation': 0, 'vaccination': 0, 'vaccine': 0, 'vacuolar': 0, 'vacuole': 0, 'vacuous': 1, 'vacuum': 0, 'vague': 0, 'vagueness': 0, 'vainly': 1, 'valance': 0, 'vale': 0, 'valet': 0, 'valiant': 0, 'validity': 0, 'valley': 0, 'valor': 0, 'valuable': 0, 'valuation': 0, 'valve': 0, 'vamp': 0, 'vampire': 1, 'van': 0, 'vane': 0, 'vanguard': 0, 'vanilla': 0, 'vanish': 0, 'vanished': 0, 'vanity': 0, 'vanquish': 0, 'vapor': 0, 'vara': 0, 'variable': 0, 'variance': 0, 'variation': 0, 'variations': 0, 'varicella': 1, 'varicose': 0, 'varied': 0, 'variegated': 0, 'variety': 0, 'vary': 0, 'vascular': 0, 'vase': 0, 'vast': 0, 'vat': 0, 'vaudeville': 0, 'vault': 0, 'vaulted': 0, 'vaulting': 0, 'veal': 0, 'vector': 0, 'veer': 0, 'vega': 0, 'vegetable': 0, 'vegetarian': 0, 'vegetarianism': 0, 'vegetation': 0, 'vegetative': 1, 'vehement': 0, 'vehicle': 0, 'veil': 0, 'veiled': 0, 'vein': 0, 'veined': 0, 'vellum': 0, 'velocity': 0, 'velour': 0, 'velvet': 0, 'velvety': 0, 'vena': 0, 'vendetta': 0, 'vendor': 0, 'veneer': 0, 'venerable': 0, 'veneration': 0, 'vengeance': 0, 'vengeful': 0, 'venison': 0, 'venom': 1, 'venomous': 1, 'venous': 0, 'vent': 0, 'ventilation': 0, 'ventilator': 0, 'ventricle': 0, 'ventricular': 0, 'venture': 0, 'venue': 0, 'veracity': 0, 'veranda': 0, 'verbal': 0, 'verbatim': 0, 'verbiage': 0, 'verbose': 0, 'verbosity': 0, 'verdant': 0, 'verdict': 0, 'verge': 0, 'verification': 0, 'verified': 0, 'verify': 0, 'verily': 0, 'veritable': 0, 'vermin': 1, 'vernacular': 0, 'vernal': 0, 'veronica': 0, 'versatile': 0, 'versatility': 0, 'verse': 0, 'version': 0, 'versus': 0, 'vert': 0, 'vertebra': 0, 'vertebral': 0, 'vertex': 0, 'vertical': 0, 'vertically': 0, 'vertigo': 0, 'verve': 0, 'vesicle': 0, 'vesicular': 1, 'vessel': 0, 'vest': 0, 'vested': 0, 'vestibule': 0, 'vestige': 0, 'vet': 0, 'veteran': 0, 'veterinarian': 0, 'veto': 0, 'viability': 0, 'viable': 0, 'viaduct': 0, 'vial': 0, 'vibrate': 0, 'vibration': 0, 'vibratory': 0, 'vicar': 0, 'vicarious': 0, 'vice': 0, 'vicinity': 0, 'vicious': 1, 'victim': 0, 'victimized': 1, 'victor': 0, 'victoria': 0, 'victorious': 0, 'victory': 0, 'videotape': 0, 'vie': 0, 'view': 0, 'vigil': 0, 'vigilance': 0, 'vigilant': 0, 'vignette': 0, 'vigor': 0, 'vigorous': 0, 'viking': 0, 'villa': 0, 'village': 0, 'villager': 0, 'villain': 0, 'villainous': 1, 'vinaigrette': 0, 'vindicate': 0, 'vindicated': 0, 'vindication': 0, 'vindictive': 1, 'vinegar': 0, 'vineyard': 0, 'viola': 0, 'violation': 0, 'violence': 0, 'violent': 1, 'violently': 1, 'violet': 0, 'violin': 0, 'violinist': 0, 'viper': 0, 'virgin': 0, 'virginity': 0, 'virology': 0, 'virtual': 0, 'virtually': 0, 'virtue': 0, 'virtuoso': 0, 'virtuous': 0, 'virulence': 0, 'virus': 0, 'visa': 0, 'visage': 0, 'viscosity': 0, 'viscous': 0, 'vise': 0, 'visibility': 0, 'visible': 0, 'visibly': 0, 'vision': 0, 'visionary': 0, 'visit': 0, 'visitation': 0, 'visiting': 0, 'visitor': 0, 'visor': 0, 'vista': 0, 'visual': 0, 'visualize': 0, 'vital': 0, 'vitality': 0, 'vitreous': 0, 'vivacious': 0, 'vivid': 0, 'vixen': 0, 'vocabulary': 0, 'vocal': 0, 'vocalist': 0, 'vocation': 0, 'vogue': 0, 'voice': 0, 'voiceless': 0, 'void': 0, 'volatility': 0, 'volcanic': 0, 'volcano': 0, 'volition': 0, 'volley': 0, 'voltmeter': 0, 'volume': 0, 'voluminous': 0, 'voluntarily': 0, 'voluntary': 0, 'volunteer': 0, 'volunteering': 0, 'volunteers': 0, 'voluptuous': 0, 'vomit': 1, 'vomiting': 0, 'voodoo': 0, 'voracious': 0, 'vortex': 0, 'vote': 0, 'voting': 0, 'votive': 0, 'vouch': 0, 'voucher': 0, 'vow': 0, 'vowel': 0, 'voyage': 0, 'voyager': 0, 'vulgar': 1, 'vulgarity': 1, 'vulnerability': 0, 'vulnerable': 0, 'vulture': 1, 'wad': 0, 'wade': 0, 'wafer': 0, 'waffle': 0, 'wag': 0, 'wager': 0, 'wages': 0, 'wagon': 0, 'wail': 0, 'waist': 0, 'waistcoat': 0, 'wait': 0, 'waiter': 0, 'waiting': 0, 'waive': 0, 'wake': 0, 'walk': 0, 'walker': 0, 'wall': 0, 'wallet': 0, 'wallow': 1, 'walnut': 0, 'waltz': 0, 'wan': 0, 'wand': 0, 'wander': 0, 'wanderer': 0, 'wandering': 0, 'wane': 0, 'waning': 0, 'wanting': 0, 'war': 0, 'warbler': 0, 'ward': 0, 'warden': 0, 'wardrobe': 0, 'ware': 0, 'warehouse': 0, 'warfare': 0, 'warlike': 0, 'warlock': 0, 'warming': 0, 'warn': 0, 'warned': 0, 'warning': 0, 'warp': 0, 'warped': 0, 'warrant': 0, 'warranted': 0, 'warrants': 0, 'warranty': 0, 'warren': 0, 'warrior': 0, 'wart': 1, 'wary': 0, 'wash': 0, 'washing': 0, 'washout': 0, 'wasp': 0, 'waste': 1, 'wasted': 1, 'wasteful': 1, 'wasting': 1, 'watch': 0, 'watchdog': 0, 'watchful': 0, 'watchman': 0, 'water': 0, 'watercourse': 0, 'watered': 0, 'waterproof': 0, 'waterworks': 0, 'watery': 0, 'wave': 0, 'waver': 0, 'wavering': 0, 'waves': 0, 'wavy': 0, 'wax': 0, 'waxy': 0, 'ways': 0, 'wayward': 0, 'weakened': 0, 'weakly': 0, 'weakness': 0, 'wealth': 0, 'wealthy': 0, 'weapon': 0, 'wear': 0, 'wearily': 0, 'weariness': 0, 'wearing': 0, 'weary': 0, 'weather': 0, 'weathered': 0, 'weatherproof': 0, 'weave': 0, 'web': 0, 'wed': 0, 'wedded': 0, 'wedge': 0, 'wee': 0, 'weed': 0, 'weeding': 0, 'weeds': 0, 'weedy': 0, 'week': 0, 'weekly': 0, 'weep': 0, 'weeping': 0, 'weigh': 0, 'weighing': 0, 'weight': 1, 'weightless': 0, 'weights': 0, 'weighty': 0, 'weir': 0, 'weird': 1, 'weirdo': 0, 'welcomed': 0, 'weld': 0, 'welfare': 0, 'wellhead': 0, 'welt': 0, 'wen': 0, 'wench': 1, 'western': 0, 'wet': 0, 'whack': 0, 'whale': 0, 'wham': 0, 'wharf': 0, 'whatsoever': 0, 'wheel': 0, 'wheels': 0, 'whereabouts': 0, 'wherefore': 0, 'wherewith': 0, 'wherewithal': 0, 'whet': 0, 'whiff': 0, 'whilst': 0, 'whim': 0, 'whimper': 0, 'whimsical': 0, 'whimsy': 0, 'whine': 1, 'whip': 0, 'whirl': 0, 'whirlpool': 0, 'whirlwind': 0, 'whisk': 0, 'whisker': 0, 'whisky': 0, 'whisper': 0, 'whispered': 0, 'whistle': 0, 'whit': 0, 'white': 0, 'whiteness': 0, 'whitish': 0, 'whiz': 0, 'wholesome': 0, 'wholly': 0, 'whoop': 0, 'whopping': 0, 'whore': 1, 'wick': 0, 'wicked': 0, 'wickedness': 1, 'wicker': 0, 'wicket': 0, 'wide': 0, 'widely': 0, 'widen': 0, 'widespread': 0, 'widow': 0, 'widower': 0, 'width': 0, 'wield': 0, 'wife': 0, 'wig': 0, 'wight': 0, 'wild': 0, 'wildcat': 0, 'wilderness': 0, 'wildfire': 0, 'willful': 0, 'willingly': 0, 'willingness': 0, 'willow': 0, 'wilted': 0, 'wily': 0, 'wimp': 1, 'wimpy': 1, 'wince': 1, 'winch': 0, 'wind': 0, 'windfall': 0, 'winding': 0, 'windmill': 0, 'window': 0, 'windy': 0, 'wine': 0, 'wing': 0, 'winged': 0, 'wink': 0, 'winner': 0, 'winning': 1, 'winnings': 0, 'winter': 0, 'wintry': 0, 'wipe': 0, 'wire': 0, 'wireless': 0, 'wis': 0, 'wisdom': 0, 'wise': 0, 'wishful': 0, 'wistful': 0, 'wit': 0, 'witch': 1, 'witchcraft': 0, 'withal': 0, 'withdraw': 0, 'withdrawal': 0, 'wither': 0, 'withered': 1, 'withstand': 0, 'witness': 0, 'wits': 0, 'witty': 0, 'wizard': 0, 'woe': 1, 'woeful': 0, 'woefully': 1, 'woman': 0, 'womanhood': 0, 'womanly': 0, 'womb': 0, 'wonderful': 0, 'wonderfully': 0, 'wondrous': 0, 'wont': 0, 'woo': 0, 'wood': 0, 'woodcut': 0, 'wooden': 0, 'woodlands': 0, 'woody': 0, 'wooing': 0, 'wool': 0, 'woolly': 0, 'wop': 0, 'word': 0, 'wording': 0, 'words': 0, 'wordy': 0, 'work': 0, 'workbook': 0, 'worker': 0, 'working': 0, 'workman': 0, 'workmanship': 0, 'workplace': 0, 'works': 0, 'workshop': 0, 'world': 0, 'worldly': 0, 'worldwide': 0, 'worm': 0, 'worn': 0, 'worried': 0, 'worry': 0, 'worrying': 0, 'worse': 0, 'worsening': 1, 'worship': 0, 'worth': 0, 'worthless': 1, 'worthy': 0, 'wot': 0, 'wound': 0, 'wrangler': 0, 'wrangling': 1, 'wrap': 0, 'wrapper': 0, 'wrapping': 0, 'wrath': 0, 'wreak': 0, 'wreath': 0, 'wreck': 1, 'wrecked': 0, 'wrench': 0, 'wrest': 0, 'wrestle': 0, 'wrestler': 0, 'wrestling': 0, 'wretch': 1, 'wretched': 1, 'wright': 0, 'wring': 0, 'wrinkle': 0, 'wrinkled': 0, 'wrist': 0, 'wristband': 0, 'wristwatch': 0, 'writ': 0, 'write': 0, 'writer': 0, 'writing': 0, 'written': 0, 'wrong': 0, 'wrongdoing': 1, 'wrongful': 1, 'wrongly': 0, 'wrought': 0, 'wry': 0, 'xenophobia': 0, 'xerox': 0, 'yacht': 0, 'yachting': 0, 'yak': 0, 'yam': 0, 'yank': 0, 'yard': 0, 'yarn': 0, 'yaw': 0, 'yawn': 0, 'yawning': 0, 'yea': 0, 'year': 0, 'yearbook': 0, 'yearling': 0, 'yearly': 0, 'yearn': 0, 'yearning': 0, 'years': 0, 'yeast': 0, 'yell': 0, 'yellow': 0, 'yellows': 0, 'yelp': 0, 'yeoman': 0, 'yesterday': 0, 'yesteryear': 0, 'yew': 0, 'yield': 0, 'yielding': 0, 'yogi': 0, 'yoke': 0, 'yolk': 0, 'yon': 0, 'yonder': 0, 'young': 0, 'younger': 0, 'youth': 0, 'zany': 0, 'zap': 0, 'zeal': 0, 'zealot': 0, 'zealous': 0, 'zebra': 0, 'zenith': 0, 'zephyr': 0, 'zeppelin': 0, 'zest': 0, 'zip': 0, 'zodiac': 0, 'zone': 0, 'zoo': 0, 'zoological': 0, 'zoology': 0, 'zoom': 0}
#For each record
#For each word in record
#Get the word score (score is a number if the word is in Lexicon, 0 if not)
#Add all the scores and find the ploarity
disgustnrc = []
strength =[]
for record in corpus:
#print("record", record)
score = 0
words = record.replace("'","").lower().split()
for word in words:
#print("word", word)
if word in (lexicons):
score = score + lexicons[word]
#print("score",score)
strength.append(score)
#print('strength',strength)
if (score > 0):
disgustnrc.append('1')
else:
disgustnrc.append('0')
#else:
# prediction.append('neutral')
print(disgustnrc)
#print(prediction)
['0', '1', '1', '0', '0', '0', '1', '0', '0', '1', '0', '0', '0', '0', '1', '0', '1', '0', '1', '1', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '1', '0', '1', '1', '0', '0', '1', '0', '1', '0', '0', '1', '0', '1', '1', '0', '1', '0', '0', '0', '0', '0', '1', '0', '1', '0', '0', '0', '0', '1', '0', '0', '1', '0', '0', '0', '0', '0', '1', '0', '0', '1', '1', '0', '1', '1', '1', '0', '0', '0', '1', '1', '0', '0', '0', '0', '1', '1', '0', '1', '0', '0', '1', '1', '0', '0', '1', '0', '0', '1', '0', '0', '1', '1', '0', '1', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '1', '1', '0', '1', '1', '0', '0', '0', '0', '0', '1', '0', '0', '1', '0', '0', '1', '1', '0', '0', '0', '0', '1', '0', '1', '0', '1', '0', '1', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '1', '0', '0', '0', '1', '0', '0', '0', '0', '0', '1', '0', '0', '0', '1', '0', '0', '1', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '1', '0', '0', '0', '1', '1', '1', '0', '1', '0', '1', '0', '0', '1', '0', '0', '1', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '1', '0', '1', '0', '0', '1', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '1', '0', '0', '1', '0', '1', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '1', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '1', '1', '1', '1', '1', '0', '0', '0', '1', '0', '1', '1', '0', '1', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '1', '0', '0', '0', '1', '0', '1', '1', '1', '1', '0', '0', '0', '0', '1', '0', '1', '0', '0', '0', '1', '1', '0', '0', '0', '0', '0', '0', '0', '1', '1', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '1', '1', '0', '0', '1', '0', '1', '1', '0', '0', '0', '0', '1', '0', '0', '1', '0', '1', '0', '0', '0', '1', '0', '1', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '1', '1', '0', '1', '0', '0', '1', '1', '0', '0', '0', '1', '0', '1', '0', '0', '1', '1', '0', '1', '0', '0', '1', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '1', '0', '1', '1', '0', '1', '1', '0', '0', '1', '1', '0', '0', '1', '0', '1', '1', '1', '1', '0', '0', '0', '0', '0', '0', '1', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '1', '1', '0', '0', '0', '0', '0', '0', '0', '1', '1', '0', '1', '1', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '1', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', 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df_new['disgustnrc']= disgustnrc
df_new.head()
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | tokenized_docs_no_stopwords | preprocessed_docs | word_final | strength_affin | prediction_affin | positivenrc | negativenrc | angernrc | anticipationnrc | disgustnrc | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | case id worst poor customer service giving res... | -2 | negative | 1 | 1 | 1 | 0 | 0 |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | ['please', 'dont', 'install', 'this', 'app', '... | ['please', 'dont', 'install', 'app', 'people',... | ['please', 'dont', 'install', 'app', 'people',... | please dont install app people stole informati... | -3 | negative | 1 | 1 | 0 | 1 | 1 |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... | ['dont', 'waste', 'your', 'time', 'and', 'mone... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | dont waste time money woohoo payment successfu... | 9 | positive | 1 | 1 | 1 | 1 | 1 |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | worst customer supportthey wont pick call wont... | -5 | negative | 1 | 0 | 0 | 1 | 0 |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... | ['was', 'a', 'happy', 'customer', 'till', 'i',... | ['happy', 'customer', 'till', 'faced', 'error'... | ['happy', 'customer', 'till', 'faced', 'error'... | happy customer till faced error guess even don... | 0 | neutral | 1 | 1 | 0 | 1 | 0 |
#Read the lexicon file
lex_file = open("D:\\11 Project\\Project\\NRC_file - Fear.csv")
lexicons = {}
records = lex_file.readlines()
for record in records:
#print(record) # line contains newline charecter
#print(record.rstrip('\n').split(",")) - to remove new line charecter
lexicons[record.rstrip('\n').split(",")[0]] = int(record.rstrip('\n').split(",")[1])
print(lexicons)
{'aback': 0, 'abacus': 0, 'abandon': 1, 'abandoned': 1, 'abandonment': 1, 'abate': 0, 'abatement': 0, 'abba': 0, 'abbot': 0, 'abbreviate': 0, 'abbreviation': 0, 'abdomen': 0, 'abdominal': 0, 'abduction': 1, 'aberrant': 0, 'aberration': 0, 'abeyance': 0, 'abhor': 1, 'abhorrent': 1, 'abide': 0, 'ability': 0, 'abject': 0, 'ablation': 0, 'ablaze': 0, 'abnormal': 0, 'aboard': 0, 'abode': 0, 'abolish': 0, 'abolition': 0, 'abominable': 1, 'abomination': 1, 'aboriginal': 0, 'abort': 0, 'abortion': 1, 'abortive': 0, 'abound': 0, 'abovementioned': 0, 'abrasion': 0, 'abroad': 0, 'abrogate': 0, 'abrupt': 0, 'abruptly': 0, 'abscess': 0, 'absence': 1, 'absent': 0, 'absentee': 0, 'absenteeism': 0, 'absinthe': 0, 'absolute': 0, 'absolution': 0, 'absorbed': 0, 'absorbent': 0, 'absorbing': 0, 'absorption': 0, 'abstain': 0, 'abstention': 0, 'abstinence': 0, 'abstract': 0, 'abstraction': 0, 'absurd': 0, 'absurdity': 0, 'abundance': 0, 'abundant': 0, 'abuse': 1, 'abutment': 0, 'aby': 0, 'abysmal': 0, 'abyss': 1, 'academic': 0, 'academy': 0, 'accede': 0, 'accelerate': 0, 'acceleration': 0, 'accent': 0, 'accentuate': 0, 'accept': 0, 'acceptable': 0, 'acceptance': 0, 'access': 0, 'accessible': 0, 'accession': 0, 'accessory': 0, 'accident': 1, 'accidental': 1, 'accidentally': 0, 'accolade': 0, 'accommodate': 0, 'accommodation': 0, 'accompaniment': 0, 'accompany': 0, 'accompanying': 0, 'accomplice': 0, 'accomplish': 0, 'accomplished': 0, 'accomplishment': 0, 'accord': 0, 'accordance': 0, 'accordion': 0, 'account': 0, 'accountability': 0, 'accountable': 0, 'accountant': 0, 'accounting': 0, 'accounts': 0, 'accredited': 0, 'accretion': 0, 'accrue': 0, 'accueil': 0, 'accumulate': 0, 'accumulation': 0, 'accuracy': 0, 'accurate': 0, 'accursed': 1, 'accusation': 0, 'accusative': 0, 'accused': 1, 'accuser': 1, 'accusing': 1, 'accustomed': 0, 'ace': 0, 'acetic': 0, 'ache': 0, 'achieve': 0, 'achievement': 0, 'aching': 0, 'acid': 0, 'acidity': 0, 'acknowledge': 0, 'acknowledged': 0, 'acknowledgment': 0, 'acme': 0, 'acoustic': 0, 'acoustics': 0, 'acquaint': 0, 'acquaintance': 0, 'acquainted': 0, 'acquiescence': 0, 'acquire': 0, 'acquiring': 0, 'acquisition': 0, 'acquisitions': 0, 'acreage': 0, 'acres': 0, 'acrobat': 1, 'act': 0, 'acting': 0, 'action': 0, 'actionable': 0, 'active': 0, 'activity': 0, 'actor': 0, 'actual': 0, 'actuality': 0, 'actuary': 0, 'acuity': 0, 'acumen': 0, 'acupuncture': 0, 'acutely': 0, 'adage': 0, 'adamant': 0, 'adapt': 0, 'adaptable': 0, 'add': 0, 'added': 0, 'addendum': 0, 'adder': 1, 'addiction': 0, 'addition': 0, 'additional': 0, 'additive': 0, 'address': 0, 'addressee': 0, 'addresses': 0, 'adept': 0, 'adequacy': 0, 'adequate': 0, 'adhere': 0, 'adherence': 0, 'adherent': 0, 'adhering': 0, 'adhesion': 0, 'adhesive': 0, 'adieu': 0, 'adipose': 0, 'adjacency': 0, 'adjacent': 0, 'adjective': 0, 'adjoining': 0, 'adjourn': 0, 'adjournment': 0, 'adjudicate': 1, 'adjudication': 0, 'adjunct': 0, 'adjust': 0, 'adjustment': 0, 'adjuvant': 0, 'administer': 0, 'administration': 0, 'administrative': 0, 'admirable': 0, 'admiral': 0, 'admiralty': 0, 'admiration': 0, 'admire': 0, 'admirer': 0, 'admissibility': 0, 'admissible': 0, 'admission': 0, 'admit': 0, 'admittance': 0, 'admitted': 0, 'admitting': 0, 'admixture': 0, 'admonition': 1, 'ado': 0, 'adobe': 0, 'adolescence': 0, 'adolescent': 0, 'adopt': 0, 'adoption': 0, 'adorable': 0, 'adoration': 0, 'adore': 0, 'adorn': 0, 'adornment': 0, 'adrift': 1, 'adult': 0, 'adulterated': 0, 'adultery': 0, 'advance': 1, 'advanced': 0, 'advancement': 0, 'advancing': 0, 'advantage': 0, 'advantageous': 0, 'advent': 0, 'adventure': 0, 'adventurer': 0, 'adventurous': 0, 'adversary': 0, 'adverse': 1, 'adversity': 1, 'advertise': 0, 'advertisement': 0, 'advice': 0, 'advisable': 0, 'advise': 0, 'advised': 0, 'advisement': 0, 'adviser': 0, 'advocacy': 0, 'advocate': 0, 'aegis': 0, 'aeration': 0, 'aerial': 0, 'aerodrome': 0, 'aerodynamics': 0, 'aeronautics': 0, 'aeroplane': 0, 'aesthetic': 0, 'aesthetics': 0, 'aetiology': 0, 'afar': 0, 'affable': 0, 'affair': 0, 'affecting': 0, 'affection': 0, 'affections': 0, 'affiche': 0, 'affidavit': 0, 'affiliated': 0, 'affiliation': 0, 'affinity': 0, 'affirm': 0, 'affirmation': 0, 'affirmative': 0, 'affirmatively': 0, 'affix': 0, 'afflict': 1, 'afflicted': 0, 'affliction': 1, 'affluence': 0, 'affluent': 0, 'afford': 0, 'affront': 1, 'afield': 0, 'afore': 0, 'aforementioned': 0, 'aforesaid': 0, 'afraid': 1, 'afresh': 0, 'aft': 0, 'aftermath': 1, 'afternoon': 0, 'aftertaste': 0, 'afterthought': 0, 'aga': 1, 'agate': 0, 'age': 0, 'aged': 0, 'agency': 0, 'agent': 0, 'agglomeration': 0, 'aggravated': 0, 'aggravating': 0, 'aggravation': 0, 'aggregate': 0, 'aggregation': 0, 'aggression': 1, 'aggressive': 1, 'aggressor': 1, 'aghast': 1, 'agile': 0, 'agility': 0, 'agitated': 0, 'agitation': 0, 'agnostic': 0, 'ago': 0, 'agonizing': 1, 'agony': 1, 'agree': 0, 'agreeable': 0, 'agreed': 0, 'agreeing': 0, 'agreement': 0, 'agricultural': 0, 'agriculture': 0, 'aground': 0, 'agua': 0, 'ahead': 0, 'aid': 0, 'aiding': 0, 'ail': 0, 'ailing': 1, 'ailment': 0, 'aim': 0, 'aimless': 0, 'air': 0, 'airbag': 0, 'airlift': 0, 'airline': 0, 'airman': 0, 'airplane': 0, 'airport': 0, 'airs': 0, 'airship': 0, 'aisle': 0, 'ait': 0, 'ajar': 0, 'akin': 0, 'alabaster': 0, 'alarm': 1, 'alarming': 1, 'alb': 0, 'album': 0, 'alchemy': 0, 'alcohol': 0, 'alcoholism': 1, 'alcove': 0, 'alert': 0, 'alertness': 1, 'alerts': 1, 'alfalfa': 0, 'algebra': 0, 'algebraic': 0, 'algorithm': 0, 'alibi': 0, 'alien': 1, 'alienate': 0, 'alienated': 0, 'alienation': 1, 'alight': 0, 'aligned': 0, 'alignment': 0, 'alike': 0, 'alimentation': 0, 'alimony': 0, 'aliquot': 0, 'alive': 0, 'alkali': 0, 'alkaloids': 0, 'allay': 0, 'allegation': 0, 'allege': 0, 'alleged': 0, 'allegiance': 0, 'allegorical': 0, 'allegory': 0, 'allegro': 0, 'alleviate': 0, 'alleviation': 0, 'alley': 0, 'alliance': 0, 'allied': 0, 'alligator': 0, 'allocate': 0, 'allocation': 0, 'allot': 0, 'allotment': 0, 'allowable': 0, 'allowance': 0, 'allowed': 0, 'alloy': 0, 'allure': 0, 'alluring': 0, 'allusion': 0, 'alluvial': 0, 'ally': 0, 'almanac': 0, 'almighty': 0, 'aloft': 0, 'aloha': 0, 'alongside': 0, 'aloof': 0, 'aloud': 0, 'alphabet': 0, 'alphabetical': 0, 'altar': 0, 'alter': 0, 'alteration': 0, 'altercation': 0, 'altered': 0, 'alternate': 0, 'alternative': 0, 'altitude': 0, 'alto': 0, 'altogether': 0, 'alumnus': 0, 'alveolar': 0, 'amalgam': 0, 'amalgamation': 0, 'amass': 0, 'amateur': 0, 'amaze': 0, 'amazement': 0, 'amazingly': 0, 'ambassador': 0, 'amber': 0, 'ambient': 0, 'ambiguity': 0, 'ambiguous': 0, 'ambit': 0, 'ambition': 0, 'ambitious': 0, 'ambulance': 1, 'ambush': 1, 'ameliorate': 0, 'amen': 0, 'amenable': 0, 'amend': 0, 'amendment': 0, 'amends': 0, 'amenity': 0, 'amethyst': 0, 'amiable': 0, 'amicable': 0, 'amid': 0, 'amidst': 0, 'ammonia': 0, 'ammunition': 0, 'amnesia': 0, 'amnesty': 0, 'amorphous': 0, 'amortization': 0, 'amount': 0, 'amour': 0, 'ampersand': 0, 'amphetamines': 0, 'amphibian': 0, 'amphibious': 0, 'amphitheater': 0, 'amplification': 0, 'amplify': 0, 'amplitude': 0, 'amply': 0, 'amputation': 0, 'amulet': 0, 'amuse': 0, 'amused': 0, 'amusement': 0, 'amusing': 0, 'ana': 0, 'anaconda': 1, 'anaesthesia': 0, 'anaesthetic': 0, 'anal': 0, 'analgesic': 0, 'analogous': 0, 'analogue': 0, 'analogy': 0, 'analysis': 0, 'analyst': 0, 'analytic': 0, 'analyze': 0, 'analyzer': 0, 'anarchism': 1, 'anarchist': 1, 'anarchy': 1, 'anastomosis': 0, 'anathema': 1, 'anatomic': 0, 'anatomy': 0, 'ancestor': 0, 'ancestral': 0, 'ancestry': 0, 'anchor': 0, 'anchorage': 0, 'ancient': 0, 'ancillary': 0, 'androgen': 0, 'anemone': 0, 'anew': 0, 'angel': 0, 'angelic': 0, 'anger': 0, 'angina': 1, 'angiography': 0, 'angle': 0, 'angling': 0, 'angry': 0, 'anguish': 1, 'angular': 0, 'anhydrous': 0, 'animal': 0, 'animate': 0, 'animated': 0, 'animation': 0, 'animosity': 1, 'animus': 0, 'ankle': 0, 'annals': 0, 'annex': 0, 'annexation': 0, 'annexe': 0, 'annihilate': 1, 'annihilated': 1, 'annihilation': 1, 'annotate': 0, 'annotation': 0, 'announce': 0, 'announcement': 0, 'annoy': 0, 'annoyance': 0, 'annoying': 0, 'annuity': 0, 'annul': 0, 'annular': 0, 'annulment': 0, 'annulus': 0, 'anointing': 0, 'anomalous': 0, 'anomaly': 1, 'anon': 0, 'anonymous': 0, 'answer': 0, 'answerable': 0, 'answering': 0, 'ant': 0, 'antagonism': 0, 'antagonist': 0, 'antagonistic': 0, 'ante': 0, 'antecedent': 0, 'antelope': 0, 'antenna': 0, 'anterior': 0, 'anthem': 0, 'anthology': 0, 'anthrax': 1, 'anthropology': 0, 'antibiotic': 0, 'antibiotics': 0, 'antichrist': 1, 'anticipation': 0, 'anticipatory': 0, 'antidote': 0, 'antifungal': 0, 'antimony': 0, 'antipathy': 0, 'antiquarian': 0, 'antiquated': 0, 'antique': 0, 'antiquity': 0, 'antiseptic': 0, 'antisocial': 1, 'antithesis': 0, 'antithetical': 0, 'antiviral': 0, 'antler': 0, 'anvil': 0, 'anxiety': 1, 'anxious': 1, 'aorta': 0, 'apace': 0, 'apache': 1, 'apartment': 0, 'apathetic': 0, 'apathy': 0, 'ape': 0, 'aperture': 0, 'apex': 0, 'aphid': 0, 'apiece': 0, 'aplomb': 0, 'apocalyptic': 0, 'apologetic': 0, 'apologist': 0, 'apologize': 0, 'apology': 0, 'apostasy': 0, 'apostate': 0, 'apostle': 0, 'apostolic': 0, 'apostrophe': 0, 'appalling': 1, 'apparatus': 0, 'apparel': 0, 'apparently': 0, 'apparition': 1, 'appeal': 0, 'appearance': 0, 'appease': 0, 'appellant': 0, 'append': 0, 'appendage': 0, 'appendicitis': 1, 'appendix': 0, 'appetite': 0, 'appetizer': 0, 'applause': 0, 'apple': 0, 'appliance': 0, 'appliances': 0, 'applicability': 0, 'applicable': 0, 'applicant': 0, 'application': 0, 'apply': 0, 'appoint': 0, 'appointment': 0, 'appointments': 0, 'apportion': 0, 'apportionment': 0, 'appraise': 0, 'appreciable': 0, 'appreciation': 0, 'apprehend': 1, 'apprehension': 1, 'apprehensive': 1, 'apprentice': 0, 'apprenticeship': 0, 'approach': 0, 'approaching': 0, 'approbation': 0, 'appropriation': 0, 'approval': 0, 'approve': 0, 'approving': 0, 'approximate': 0, 'approximately': 0, 'approximating': 0, 'approximation': 0, 'appurtenances': 0, 'apron': 0, 'apt': 0, 'aptitude': 0, 'aqua': 0, 'aquamarine': 0, 'aquarium': 0, 'aquatic': 0, 'aqueduct': 0, 'aqueous': 0, 'arable': 0, 'arbiter': 0, 'arbitrate': 0, 'arbitration': 0, 'arbitrator': 0, 'arbor': 0, 'arc': 0, 'arcade': 0, 'arch': 0, 'archaeological': 0, 'archaeologist': 0, 'archaeology': 0, 'archaic': 0, 'archbishop': 0, 'arched': 0, 'archer': 0, 'archery': 0, 'archetype': 0, 'archipelago': 0, 'architect': 0, 'architecture': 0, 'archive': 0, 'arctic': 0, 'ardent': 0, 'ardor': 0, 'arduous': 0, 'area': 0, 'arena': 0, 'areola': 0, 'argent': 0, 'argue': 0, 'argument': 0, 'argumentation': 0, 'argumentative': 0, 'arguments': 0, 'arid': 0, 'aristocracy': 0, 'aristocrat': 0, 'aristocratic': 0, 'arithmetic': 0, 'ark': 0, 'arm': 0, 'armada': 0, 'armament': 1, 'armaments': 1, 'armature': 0, 'armed': 1, 'armor': 1, 'armored': 1, 'armory': 0, 'arms': 0, 'army': 0, 'aroma': 0, 'arousal': 0, 'arouse': 0, 'arraignment': 1, 'arrange': 0, 'arranged': 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'vanished': 1, 'vanity': 0, 'vanquish': 0, 'vapor': 0, 'vara': 0, 'variable': 0, 'variance': 0, 'variation': 0, 'variations': 0, 'varicella': 1, 'varicose': 0, 'varied': 0, 'variegated': 0, 'variety': 0, 'vary': 0, 'vascular': 0, 'vase': 0, 'vast': 0, 'vat': 0, 'vaudeville': 0, 'vault': 0, 'vaulted': 0, 'vaulting': 0, 'veal': 0, 'vector': 0, 'veer': 1, 'vega': 0, 'vegetable': 0, 'vegetarian': 0, 'vegetarianism': 0, 'vegetation': 0, 'vegetative': 0, 'vehement': 1, 'vehicle': 0, 'veil': 0, 'veiled': 0, 'vein': 0, 'veined': 0, 'vellum': 0, 'velocity': 0, 'velour': 0, 'velvet': 0, 'velvety': 0, 'vena': 0, 'vendetta': 1, 'vendor': 0, 'veneer': 0, 'venerable': 0, 'veneration': 0, 'vengeance': 0, 'vengeful': 1, 'venison': 0, 'venom': 1, 'venomous': 1, 'venous': 0, 'vent': 0, 'ventilation': 0, 'ventilator': 0, 'ventricle': 0, 'ventricular': 0, 'venture': 0, 'venue': 0, 'veracity': 0, 'veranda': 0, 'verbal': 0, 'verbatim': 0, 'verbiage': 0, 'verbose': 0, 'verbosity': 0, 'verdant': 0, 'verdict': 1, 'verge': 1, 'verification': 0, 'verified': 0, 'verify': 0, 'verily': 0, 'veritable': 0, 'vermin': 1, 'vernacular': 0, 'vernal': 0, 'veronica': 0, 'versatile': 0, 'versatility': 0, 'verse': 0, 'version': 0, 'versus': 0, 'vert': 0, 'vertebra': 0, 'vertebral': 0, 'vertex': 0, 'vertical': 0, 'vertically': 0, 'vertigo': 1, 'verve': 0, 'vesicle': 0, 'vesicular': 0, 'vessel': 0, 'vest': 0, 'vested': 0, 'vestibule': 0, 'vestige': 0, 'vet': 0, 'veteran': 0, 'veterinarian': 0, 'veto': 0, 'viability': 0, 'viable': 0, 'viaduct': 0, 'vial': 0, 'vibrate': 0, 'vibration': 0, 'vibratory': 0, 'vicar': 0, 'vicarious': 0, 'vice': 0, 'vicinity': 0, 'vicious': 0, 'victim': 1, 'victimized': 1, 'victor': 0, 'victoria': 0, 'victorious': 0, 'victory': 0, 'videotape': 0, 'vie': 0, 'view': 0, 'vigil': 0, 'vigilance': 0, 'vigilant': 1, 'vignette': 0, 'vigor': 0, 'vigorous': 0, 'viking': 0, 'villa': 0, 'village': 0, 'villager': 0, 'villain': 1, 'villainous': 1, 'vinaigrette': 0, 'vindicate': 0, 'vindicated': 0, 'vindication': 0, 'vindictive': 0, 'vinegar': 0, 'vineyard': 0, 'viola': 0, 'violation': 1, 'violence': 1, 'violent': 1, 'violently': 1, 'violet': 0, 'violin': 0, 'violinist': 0, 'viper': 1, 'virgin': 0, 'virginity': 0, 'virology': 0, 'virtual': 0, 'virtually': 0, 'virtue': 0, 'virtuoso': 0, 'virtuous': 0, 'virulence': 1, 'virus': 0, 'visa': 0, 'visage': 0, 'viscosity': 0, 'viscous': 0, 'vise': 0, 'visibility': 0, 'visible': 0, 'visibly': 0, 'vision': 0, 'visionary': 0, 'visit': 0, 'visitation': 0, 'visiting': 0, 'visitor': 0, 'visor': 0, 'vista': 0, 'visual': 0, 'visualize': 0, 'vital': 0, 'vitality': 0, 'vitreous': 0, 'vivacious': 0, 'vivid': 0, 'vixen': 0, 'vocabulary': 0, 'vocal': 0, 'vocalist': 0, 'vocation': 0, 'vogue': 0, 'voice': 0, 'voiceless': 0, 'void': 0, 'volatility': 1, 'volcanic': 0, 'volcano': 1, 'volition': 0, 'volley': 0, 'voltmeter': 0, 'volume': 0, 'voluminous': 0, 'voluntarily': 0, 'voluntary': 0, 'volunteer': 1, 'volunteering': 0, 'volunteers': 0, 'voluptuous': 0, 'vomit': 0, 'vomiting': 0, 'voodoo': 0, 'voracious': 0, 'vortex': 0, 'vote': 0, 'voting': 0, 'votive': 0, 'vouch': 0, 'voucher': 0, 'vow': 0, 'vowel': 0, 'voyage': 0, 'voyager': 0, 'vulgar': 0, 'vulgarity': 0, 'vulnerability': 1, 'vulnerable': 0, 'vulture': 1, 'wad': 0, 'wade': 0, 'wafer': 0, 'waffle': 0, 'wag': 0, 'wager': 0, 'wages': 0, 'wagon': 0, 'wail': 1, 'waist': 0, 'waistcoat': 0, 'wait': 0, 'waiter': 0, 'waiting': 0, 'waive': 0, 'wake': 0, 'walk': 0, 'walker': 0, 'wall': 0, 'wallet': 0, 'wallow': 0, 'walnut': 0, 'waltz': 0, 'wan': 1, 'wand': 0, 'wander': 0, 'wanderer': 0, 'wandering': 0, 'wane': 0, 'waning': 0, 'wanting': 0, 'war': 1, 'warbler': 0, 'ward': 0, 'warden': 1, 'wardrobe': 0, 'ware': 1, 'warehouse': 0, 'warfare': 1, 'warlike': 1, 'warlock': 1, 'warming': 0, 'warn': 1, 'warned': 1, 'warning': 1, 'warp': 0, 'warped': 0, 'warrant': 0, 'warranted': 0, 'warrants': 0, 'warranty': 0, 'warren': 0, 'warrior': 1, 'wart': 0, 'wary': 1, 'wash': 0, 'washing': 0, 'washout': 0, 'wasp': 0, 'waste': 0, 'wasted': 0, 'wasteful': 0, 'wasting': 1, 'watch': 1, 'watchdog': 0, 'watchful': 0, 'watchman': 0, 'water': 0, 'watercourse': 0, 'watered': 0, 'waterproof': 0, 'waterworks': 0, 'watery': 0, 'wave': 0, 'waver': 1, 'wavering': 0, 'waves': 0, 'wavy': 0, 'wax': 0, 'waxy': 0, 'ways': 0, 'wayward': 0, 'weakened': 0, 'weakly': 1, 'weakness': 0, 'wealth': 0, 'wealthy': 0, 'weapon': 0, 'wear': 0, 'wearily': 0, 'weariness': 0, 'wearing': 0, 'weary': 0, 'weather': 0, 'weathered': 0, 'weatherproof': 0, 'weave': 0, 'web': 0, 'wed': 0, 'wedded': 0, 'wedge': 0, 'wee': 0, 'weed': 0, 'weeding': 0, 'weeds': 0, 'weedy': 0, 'week': 0, 'weekly': 0, 'weep': 0, 'weeping': 0, 'weigh': 0, 'weighing': 0, 'weight': 1, 'weightless': 0, 'weights': 0, 'weighty': 1, 'weir': 0, 'weird': 0, 'weirdo': 1, 'welcomed': 0, 'weld': 0, 'welfare': 0, 'wellhead': 0, 'welt': 0, 'wen': 0, 'wench': 0, 'western': 0, 'wet': 0, 'whack': 0, 'whale': 0, 'wham': 0, 'wharf': 0, 'whatsoever': 0, 'wheel': 0, 'wheels': 0, 'whereabouts': 0, 'wherefore': 0, 'wherewith': 0, 'wherewithal': 0, 'whet': 0, 'whiff': 0, 'whilst': 0, 'whim': 0, 'whimper': 1, 'whimsical': 0, 'whimsy': 0, 'whine': 0, 'whip': 0, 'whirl': 0, 'whirlpool': 1, 'whirlwind': 1, 'whisk': 0, 'whisker': 0, 'whisky': 0, 'whisper': 0, 'whispered': 0, 'whistle': 0, 'whit': 0, 'white': 0, 'whiteness': 0, 'whitish': 0, 'whiz': 0, 'wholesome': 0, 'wholly': 0, 'whoop': 0, 'whopping': 0, 'whore': 0, 'wick': 0, 'wicked': 1, 'wickedness': 0, 'wicker': 0, 'wicket': 0, 'wide': 0, 'widely': 0, 'widen': 0, 'widespread': 0, 'widow': 0, 'widower': 0, 'width': 0, 'wield': 0, 'wife': 0, 'wig': 0, 'wight': 0, 'wild': 0, 'wildcat': 0, 'wilderness': 1, 'wildfire': 1, 'willful': 0, 'willingly': 0, 'willingness': 0, 'willow': 0, 'wilted': 0, 'wily': 0, 'wimp': 1, 'wimpy': 1, 'wince': 1, 'winch': 0, 'wind': 0, 'windfall': 0, 'winding': 0, 'windmill': 0, 'window': 0, 'windy': 0, 'wine': 0, 'wing': 0, 'winged': 0, 'wink': 0, 'winner': 0, 'winning': 0, 'winnings': 0, 'winter': 0, 'wintry': 0, 'wipe': 0, 'wire': 0, 'wireless': 0, 'wis': 0, 'wisdom': 0, 'wise': 0, 'wishful': 0, 'wistful': 0, 'wit': 0, 'witch': 1, 'witchcraft': 1, 'withal': 0, 'withdraw': 0, 'withdrawal': 0, 'wither': 0, 'withered': 0, 'withstand': 1, 'witness': 0, 'wits': 0, 'witty': 0, 'wizard': 0, 'woe': 1, 'woeful': 0, 'woefully': 0, 'woman': 0, 'womanhood': 0, 'womanly': 0, 'womb': 0, 'wonderful': 0, 'wonderfully': 0, 'wondrous': 0, 'wont': 0, 'woo': 0, 'wood': 0, 'woodcut': 0, 'wooden': 0, 'woodlands': 0, 'woody': 0, 'wooing': 0, 'wool': 0, 'woolly': 0, 'wop': 0, 'word': 0, 'wording': 0, 'words': 0, 'wordy': 0, 'work': 0, 'workbook': 0, 'worker': 0, 'working': 0, 'workman': 0, 'workmanship': 0, 'workplace': 0, 'works': 0, 'workshop': 0, 'world': 0, 'worldly': 0, 'worldwide': 0, 'worm': 0, 'worn': 0, 'worried': 0, 'worry': 1, 'worrying': 1, 'worse': 1, 'worsening': 0, 'worship': 1, 'worth': 0, 'worthless': 0, 'worthy': 0, 'wot': 0, 'wound': 1, 'wrangler': 0, 'wrangling': 1, 'wrap': 0, 'wrapper': 0, 'wrapping': 0, 'wrath': 1, 'wreak': 0, 'wreath': 0, 'wreck': 1, 'wrecked': 1, 'wrench': 0, 'wrest': 0, 'wrestle': 0, 'wrestler': 0, 'wrestling': 0, 'wretch': 0, 'wretched': 0, 'wright': 0, 'wring': 0, 'wrinkle': 0, 'wrinkled': 0, 'wrist': 0, 'wristband': 0, 'wristwatch': 0, 'writ': 0, 'write': 0, 'writer': 0, 'writing': 0, 'written': 0, 'wrong': 0, 'wrongdoing': 0, 'wrongful': 0, 'wrongly': 1, 'wrought': 0, 'wry': 0, 'xenophobia': 1, 'xerox': 0, 'yacht': 0, 'yachting': 0, 'yak': 0, 'yam': 0, 'yank': 0, 'yard': 0, 'yarn': 0, 'yaw': 0, 'yawn': 0, 'yawning': 0, 'yea': 0, 'year': 0, 'yearbook': 0, 'yearling': 0, 'yearly': 0, 'yearn': 0, 'yearning': 0, 'years': 0, 'yeast': 0, 'yell': 1, 'yellow': 0, 'yellows': 0, 'yelp': 1, 'yeoman': 0, 'yesterday': 0, 'yesteryear': 0, 'yew': 0, 'yield': 0, 'yielding': 0, 'yogi': 0, 'yoke': 0, 'yolk': 0, 'yon': 0, 'yonder': 0, 'young': 0, 'younger': 0, 'youth': 1, 'zany': 0, 'zap': 0, 'zeal': 0, 'zealot': 0, 'zealous': 0, 'zebra': 0, 'zenith': 0, 'zephyr': 0, 'zeppelin': 0, 'zest': 0, 'zip': 0, 'zodiac': 0, 'zone': 0, 'zoo': 0, 'zoological': 0, 'zoology': 0, 'zoom': 0}
#For each record
#For each word in record
#Get the word score (score is a number if the word is in Lexicon, 0 if not)
#Add all the scores and find the ploarity
fearnrc = []
strength =[]
for record in corpus:
#print("record", record)
score = 0
words = record.replace("'","").lower().split()
for word in words:
#print("word", word)
if word in (lexicons):
score = score + lexicons[word]
#print("score",score)
strength.append(score)
#print('strength',strength)
if (score > 0):
fearnrc.append('1')
else:
fearnrc.append('0')
#else:
# prediction.append('neutral')
print(fearnrc)
#print(prediction)
['1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '1', '0', '0', '0', '1', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '1', '1', '1', '1', '0', '0', '1', '0', '1', '0', '0', '0', '0', '0', '1', '0', '1', '0', '1', '0', '0', '0', '1', '0', '1', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '1', '0', '1', '0', '1', '1', '0', '1', '0', '1', '1', '1', '0', '0', '0', '0', '0', '1', '1', '0', '0', '0', '0', '0', '1', '0', '0', '1', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '1', '0', '1', '0', '0', '1', '0', '1', '0', '1', '1', '1', '0', '0', '0', '0', '0', '1', '0', '1', '1', '0', '0', '1', '0', '0', '0', '0', '0', '1', '0', '1', '1', '0', '0', '1', '0', '0', '1', '0', '1', '1', '0', '0', '0', '0', '0', '0', '1', '1', '0', '0', '0', '0', '1', '0', '0', '0', '1', '0', '0', '0', '0', '1', '1', '0', '0', '0', '1', '0', '0', '1', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '1', '0', '0', '0', '1', '1', '1', '0', 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'0', '1', '1', '0', '0', '0', '0', '0', '0', '0', '1', '1', '0', '0', '0', '0', '0', '0', '1', '0', '1', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '1', '1', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '1', '0', '0', '1', '0', '1', '0', '1', '0', '0', '0', '0', '0', '1', '0', '1', '1', '0', '0', '1', '0', '0', '0', '0', '0', '1', '0', '0', '1', '0', '1', '0', '0', '0', '0', '0', '0', '0', '1', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '1', '1', '0', '1', '0', '1', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '1', '1', '0', '0', '1', '0', '0', '0', '0', '0', '1', '1', '0', '0', '0', '0', '0', '0', '0', '1', '0', '1', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '1', '0', '0', '0', '1', '0', '0', '0', '0', '0', '1', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', 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df_new['fearnrc']= fearnrc
df_new.head()
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | tokenized_docs_no_stopwords | preprocessed_docs | word_final | strength_affin | prediction_affin | positivenrc | negativenrc | angernrc | anticipationnrc | disgustnrc | fearnrc | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | case id worst poor customer service giving res... | -2 | negative | 1 | 1 | 1 | 0 | 0 | 1 |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | ['please', 'dont', 'install', 'this', 'app', '... | ['please', 'dont', 'install', 'app', 'people',... | ['please', 'dont', 'install', 'app', 'people',... | please dont install app people stole informati... | -3 | negative | 1 | 1 | 0 | 1 | 1 | 0 |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... | ['dont', 'waste', 'your', 'time', 'and', 'mone... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | dont waste time money woohoo payment successfu... | 9 | positive | 1 | 1 | 1 | 1 | 1 | 0 |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | worst customer supportthey wont pick call wont... | -5 | negative | 1 | 0 | 0 | 1 | 0 | 0 |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... | ['was', 'a', 'happy', 'customer', 'till', 'i',... | ['happy', 'customer', 'till', 'faced', 'error'... | ['happy', 'customer', 'till', 'faced', 'error'... | happy customer till faced error guess even don... | 0 | neutral | 1 | 1 | 0 | 1 | 0 | 0 |
#Read the lexicon file
lex_file = open("D:\\11 Project\\Project\\NRC_file - Joy.csv")
lexicons = {}
records = lex_file.readlines()
for record in records:
#print(record) # line contains newline charecter
#print(record.rstrip('\n').split(",")) - to remove new line charecter
lexicons[record.rstrip('\n').split(",")[0]] = int(record.rstrip('\n').split(",")[1])
print(lexicons)
{'aback': 0, 'abacus': 0, 'abandon': 0, 'abandoned': 0, 'abandonment': 0, 'abate': 0, 'abatement': 0, 'abba': 0, 'abbot': 0, 'abbreviate': 0, 'abbreviation': 0, 'abdomen': 0, 'abdominal': 0, 'abduction': 0, 'aberrant': 0, 'aberration': 0, 'abeyance': 0, 'abhor': 0, 'abhorrent': 0, 'abide': 0, 'ability': 0, 'abject': 0, 'ablation': 0, 'ablaze': 0, 'abnormal': 0, 'aboard': 0, 'abode': 0, 'abolish': 0, 'abolition': 0, 'abominable': 0, 'abomination': 0, 'aboriginal': 0, 'abort': 0, 'abortion': 0, 'abortive': 0, 'abound': 0, 'abovementioned': 0, 'abrasion': 0, 'abroad': 0, 'abrogate': 0, 'abrupt': 0, 'abruptly': 0, 'abscess': 0, 'absence': 0, 'absent': 0, 'absentee': 0, 'absenteeism': 0, 'absinthe': 0, 'absolute': 0, 'absolution': 1, 'absorbed': 0, 'absorbent': 0, 'absorbing': 0, 'absorption': 0, 'abstain': 0, 'abstention': 0, 'abstinence': 0, 'abstract': 0, 'abstraction': 0, 'absurd': 0, 'absurdity': 0, 'abundance': 1, 'abundant': 1, 'abuse': 0, 'abutment': 0, 'aby': 0, 'abysmal': 0, 'abyss': 0, 'academic': 0, 'academy': 0, 'accede': 0, 'accelerate': 0, 'acceleration': 0, 'accent': 0, 'accentuate': 0, 'accept': 0, 'acceptable': 0, 'acceptance': 0, 'access': 0, 'accessible': 0, 'accession': 0, 'accessory': 0, 'accident': 0, 'accidental': 0, 'accidentally': 0, 'accolade': 1, 'accommodate': 0, 'accommodation': 0, 'accompaniment': 1, 'accompany': 0, 'accompanying': 0, 'accomplice': 0, 'accomplish': 1, 'accomplished': 1, 'accomplishment': 0, 'accord': 0, 'accordance': 0, 'accordion': 0, 'account': 0, 'accountability': 0, 'accountable': 0, 'accountant': 0, 'accounting': 0, 'accounts': 0, 'accredited': 0, 'accretion': 0, 'accrue': 0, 'accueil': 0, 'accumulate': 0, 'accumulation': 0, 'accuracy': 0, 'accurate': 0, 'accursed': 0, 'accusation': 0, 'accusative': 0, 'accused': 0, 'accuser': 0, 'accusing': 0, 'accustomed': 0, 'ace': 0, 'acetic': 0, 'ache': 0, 'achieve': 1, 'achievement': 1, 'aching': 0, 'acid': 0, 'acidity': 0, 'acknowledge': 0, 'acknowledged': 0, 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'aesthetics': 1, 'aetiology': 0, 'afar': 0, 'affable': 0, 'affair': 0, 'affecting': 0, 'affection': 1, 'affections': 0, 'affiche': 0, 'affidavit': 0, 'affiliated': 0, 'affiliation': 0, 'affinity': 0, 'affirm': 0, 'affirmation': 0, 'affirmative': 0, 'affirmatively': 0, 'affix': 0, 'afflict': 0, 'afflicted': 0, 'affliction': 0, 'affluence': 1, 'affluent': 0, 'afford': 0, 'affront': 0, 'afield': 0, 'afore': 0, 'aforementioned': 0, 'aforesaid': 0, 'afraid': 0, 'afresh': 0, 'aft': 0, 'aftermath': 0, 'afternoon': 0, 'aftertaste': 0, 'afterthought': 0, 'aga': 0, 'agate': 0, 'age': 0, 'aged': 0, 'agency': 0, 'agent': 0, 'agglomeration': 0, 'aggravated': 0, 'aggravating': 0, 'aggravation': 0, 'aggregate': 0, 'aggregation': 0, 'aggression': 0, 'aggressive': 0, 'aggressor': 0, 'aghast': 0, 'agile': 0, 'agility': 0, 'agitated': 0, 'agitation': 0, 'agnostic': 0, 'ago': 0, 'agonizing': 0, 'agony': 0, 'agree': 0, 'agreeable': 0, 'agreed': 0, 'agreeing': 0, 'agreement': 0, 'agricultural': 0, 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'amphetamines': 0, 'amphibian': 0, 'amphibious': 0, 'amphitheater': 0, 'amplification': 0, 'amplify': 0, 'amplitude': 0, 'amply': 0, 'amputation': 0, 'amulet': 0, 'amuse': 1, 'amused': 1, 'amusement': 1, 'amusing': 1, 'ana': 0, 'anaconda': 0, 'anaesthesia': 0, 'anaesthetic': 0, 'anal': 0, 'analgesic': 0, 'analogous': 0, 'analogue': 0, 'analogy': 0, 'analysis': 0, 'analyst': 0, 'analytic': 0, 'analyze': 0, 'analyzer': 0, 'anarchism': 0, 'anarchist': 0, 'anarchy': 0, 'anastomosis': 0, 'anathema': 0, 'anatomic': 0, 'anatomy': 0, 'ancestor': 0, 'ancestral': 0, 'ancestry': 0, 'anchor': 0, 'anchorage': 0, 'ancient': 0, 'ancillary': 0, 'androgen': 0, 'anemone': 0, 'anew': 0, 'angel': 1, 'angelic': 1, 'anger': 0, 'angina': 0, 'angiography': 0, 'angle': 0, 'angling': 0, 'angry': 0, 'anguish': 0, 'angular': 0, 'anhydrous': 0, 'animal': 0, 'animate': 0, 'animated': 1, 'animation': 0, 'animosity': 0, 'animus': 0, 'ankle': 0, 'annals': 0, 'annex': 0, 'annexation': 0, 'annexe': 0, 'annihilate': 0, 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'wheels': 0, 'whereabouts': 0, 'wherefore': 0, 'wherewith': 0, 'wherewithal': 0, 'whet': 0, 'whiff': 0, 'whilst': 0, 'whim': 1, 'whimper': 0, 'whimsical': 1, 'whimsy': 0, 'whine': 0, 'whip': 0, 'whirl': 0, 'whirlpool': 0, 'whirlwind': 0, 'whisk': 0, 'whisker': 0, 'whisky': 0, 'whisper': 0, 'whispered': 0, 'whistle': 0, 'whit': 0, 'white': 1, 'whiteness': 1, 'whitish': 0, 'whiz': 0, 'wholesome': 0, 'wholly': 0, 'whoop': 0, 'whopping': 0, 'whore': 0, 'wick': 0, 'wicked': 0, 'wickedness': 0, 'wicker': 0, 'wicket': 0, 'wide': 0, 'widely': 0, 'widen': 0, 'widespread': 0, 'widow': 0, 'widower': 0, 'width': 0, 'wield': 0, 'wife': 0, 'wig': 0, 'wight': 0, 'wild': 0, 'wildcat': 0, 'wilderness': 0, 'wildfire': 0, 'willful': 0, 'willingly': 0, 'willingness': 0, 'willow': 0, 'wilted': 0, 'wily': 0, 'wimp': 0, 'wimpy': 0, 'wince': 0, 'winch': 0, 'wind': 0, 'windfall': 0, 'winding': 0, 'windmill': 0, 'window': 0, 'windy': 0, 'wine': 0, 'wing': 0, 'winged': 0, 'wink': 0, 'winner': 1, 'winning': 1, 'winnings': 1, 'winter': 0, 'wintry': 0, 'wipe': 0, 'wire': 0, 'wireless': 0, 'wis': 0, 'wisdom': 0, 'wise': 0, 'wishful': 0, 'wistful': 0, 'wit': 0, 'witch': 0, 'witchcraft': 0, 'withal': 0, 'withdraw': 0, 'withdrawal': 0, 'wither': 0, 'withered': 0, 'withstand': 0, 'witness': 0, 'wits': 0, 'witty': 1, 'wizard': 0, 'woe': 0, 'woeful': 0, 'woefully': 0, 'woman': 0, 'womanhood': 0, 'womanly': 0, 'womb': 0, 'wonderful': 1, 'wonderfully': 1, 'wondrous': 0, 'wont': 0, 'woo': 0, 'wood': 0, 'woodcut': 0, 'wooden': 0, 'woodlands': 0, 'woody': 0, 'wooing': 0, 'wool': 0, 'woolly': 0, 'wop': 0, 'word': 0, 'wording': 0, 'words': 0, 'wordy': 0, 'work': 0, 'workbook': 0, 'worker': 0, 'working': 0, 'workman': 0, 'workmanship': 0, 'workplace': 0, 'works': 0, 'workshop': 0, 'world': 0, 'worldly': 0, 'worldwide': 0, 'worm': 0, 'worn': 0, 'worried': 0, 'worry': 0, 'worrying': 0, 'worse': 0, 'worsening': 0, 'worship': 1, 'worth': 0, 'worthless': 0, 'worthy': 0, 'wot': 0, 'wound': 0, 'wrangler': 0, 'wrangling': 0, 'wrap': 0, 'wrapper': 0, 'wrapping': 0, 'wrath': 0, 'wreak': 0, 'wreath': 0, 'wreck': 0, 'wrecked': 0, 'wrench': 0, 'wrest': 0, 'wrestle': 0, 'wrestler': 0, 'wrestling': 0, 'wretch': 0, 'wretched': 0, 'wright': 0, 'wring': 0, 'wrinkle': 0, 'wrinkled': 0, 'wrist': 0, 'wristband': 0, 'wristwatch': 0, 'writ': 0, 'write': 0, 'writer': 0, 'writing': 0, 'written': 0, 'wrong': 0, 'wrongdoing': 0, 'wrongful': 0, 'wrongly': 0, 'wrought': 0, 'wry': 0, 'xenophobia': 0, 'xerox': 0, 'yacht': 0, 'yachting': 0, 'yak': 0, 'yam': 0, 'yank': 0, 'yard': 0, 'yarn': 0, 'yaw': 0, 'yawn': 0, 'yawning': 0, 'yea': 0, 'year': 0, 'yearbook': 0, 'yearling': 0, 'yearly': 0, 'yearn': 0, 'yearning': 1, 'years': 0, 'yeast': 0, 'yell': 0, 'yellow': 0, 'yellows': 0, 'yelp': 0, 'yeoman': 0, 'yesterday': 0, 'yesteryear': 0, 'yew': 0, 'yield': 0, 'yielding': 0, 'yogi': 0, 'yoke': 0, 'yolk': 0, 'yon': 0, 'yonder': 0, 'young': 1, 'younger': 0, 'youth': 1, 'zany': 0, 'zap': 0, 'zeal': 1, 'zealot': 0, 'zealous': 1, 'zebra': 0, 'zenith': 0, 'zephyr': 0, 'zeppelin': 0, 'zest': 1, 'zip': 0, 'zodiac': 0, 'zone': 0, 'zoo': 0, 'zoological': 0, 'zoology': 0, 'zoom': 0}
#For each record
#For each word in record
#Get the word score (score is a number if the word is in Lexicon, 0 if not)
#Add all the scores and find the ploarity
joynrc = []
strength =[]
for record in corpus:
#print("record", record)
score = 0
words = record.replace("'","").lower().split()
for word in words:
#print("word", word)
if word in (lexicons):
score = score + lexicons[word]
#print("score",score)
strength.append(score)
#print('strength',strength)
if (score > 0):
joynrc.append('1')
else:
joynrc.append('0')
#else:
# prediction.append('neutral')
print(joynrc)
#print(prediction)
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df_new['joynrc']= joynrc
df_new.head()
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | tokenized_docs_no_stopwords | preprocessed_docs | word_final | strength_affin | prediction_affin | positivenrc | negativenrc | angernrc | anticipationnrc | disgustnrc | fearnrc | joynrc | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | case id worst poor customer service giving res... | -2 | negative | 1 | 1 | 1 | 0 | 0 | 1 | 0 |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | ['please', 'dont', 'install', 'this', 'app', '... | ['please', 'dont', 'install', 'app', 'people',... | ['please', 'dont', 'install', 'app', 'people',... | please dont install app people stole informati... | -3 | negative | 1 | 1 | 0 | 1 | 1 | 0 | 1 |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... | ['dont', 'waste', 'your', 'time', 'and', 'mone... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | dont waste time money woohoo payment successfu... | 9 | positive | 1 | 1 | 1 | 1 | 1 | 0 | 1 |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | worst customer supportthey wont pick call wont... | -5 | negative | 1 | 0 | 0 | 1 | 0 | 0 | 0 |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... | ['was', 'a', 'happy', 'customer', 'till', 'i',... | ['happy', 'customer', 'till', 'faced', 'error'... | ['happy', 'customer', 'till', 'faced', 'error'... | happy customer till faced error guess even don... | 0 | neutral | 1 | 1 | 0 | 1 | 0 | 0 | 1 |
#Read the lexicon file
lex_file = open("D:\\11 Project\\Project\\NRC_file - Sadness.csv")
lexicons = {}
records = lex_file.readlines()
for record in records:
#print(record) # line contains newline charecter
#print(record.rstrip('\n').split(",")) - to remove new line charecter
lexicons[record.rstrip('\n').split(",")[0]] = int(record.rstrip('\n').split(",")[1])
print(lexicons)
{'aback': 0, 'abacus': 0, 'abandon': 1, 'abandoned': 1, 'abandonment': 1, 'abate': 0, 'abatement': 0, 'abba': 0, 'abbot': 0, 'abbreviate': 0, 'abbreviation': 0, 'abdomen': 0, 'abdominal': 0, 'abduction': 1, 'aberrant': 0, 'aberration': 0, 'abeyance': 0, 'abhor': 0, 'abhorrent': 0, 'abide': 0, 'ability': 0, 'abject': 0, 'ablation': 0, 'ablaze': 0, 'abnormal': 0, 'aboard': 0, 'abode': 0, 'abolish': 0, 'abolition': 0, 'abominable': 0, 'abomination': 0, 'aboriginal': 0, 'abort': 0, 'abortion': 1, 'abortive': 1, 'abound': 0, 'abovementioned': 0, 'abrasion': 0, 'abroad': 0, 'abrogate': 0, 'abrupt': 0, 'abruptly': 0, 'abscess': 1, 'absence': 1, 'absent': 1, 'absentee': 1, 'absenteeism': 0, 'absinthe': 0, 'absolute': 0, 'absolution': 0, 'absorbed': 0, 'absorbent': 0, 'absorbing': 0, 'absorption': 0, 'abstain': 0, 'abstention': 0, 'abstinence': 0, 'abstract': 0, 'abstraction': 0, 'absurd': 0, 'absurdity': 0, 'abundance': 0, 'abundant': 0, 'abuse': 1, 'abutment': 0, 'aby': 0, 'abysmal': 1, 'abyss': 1, 'academic': 0, 'academy': 0, 'accede': 0, 'accelerate': 0, 'acceleration': 0, 'accent': 0, 'accentuate': 0, 'accept': 0, 'acceptable': 0, 'acceptance': 0, 'access': 0, 'accessible': 0, 'accession': 0, 'accessory': 0, 'accident': 1, 'accidental': 0, 'accidentally': 0, 'accolade': 0, 'accommodate': 0, 'accommodation': 0, 'accompaniment': 0, 'accompany': 0, 'accompanying': 0, 'accomplice': 0, 'accomplish': 0, 'accomplished': 0, 'accomplishment': 0, 'accord': 0, 'accordance': 0, 'accordion': 0, 'account': 0, 'accountability': 0, 'accountable': 0, 'accountant': 0, 'accounting': 0, 'accounts': 0, 'accredited': 0, 'accretion': 0, 'accrue': 0, 'accueil': 0, 'accumulate': 0, 'accumulation': 0, 'accuracy': 0, 'accurate': 0, 'accursed': 1, 'accusation': 0, 'accusative': 0, 'accused': 0, 'accuser': 0, 'accusing': 0, 'accustomed': 0, 'ace': 0, 'acetic': 0, 'ache': 1, 'achieve': 0, 'achievement': 0, 'aching': 1, 'acid': 0, 'acidity': 0, 'acknowledge': 0, 'acknowledged': 0, 'acknowledgment': 0, 'acme': 0, 'acoustic': 0, 'acoustics': 0, 'acquaint': 0, 'acquaintance': 0, 'acquainted': 0, 'acquiescence': 0, 'acquire': 0, 'acquiring': 0, 'acquisition': 0, 'acquisitions': 0, 'acreage': 0, 'acres': 0, 'acrobat': 0, 'act': 0, 'acting': 0, 'action': 0, 'actionable': 0, 'active': 0, 'activity': 0, 'actor': 0, 'actual': 0, 'actuality': 0, 'actuary': 0, 'acuity': 0, 'acumen': 0, 'acupuncture': 0, 'acutely': 0, 'adage': 0, 'adamant': 0, 'adapt': 0, 'adaptable': 0, 'add': 0, 'added': 0, 'addendum': 0, 'adder': 1, 'addiction': 0, 'addition': 0, 'additional': 0, 'additive': 0, 'address': 0, 'addressee': 0, 'addresses': 0, 'adept': 0, 'adequacy': 0, 'adequate': 0, 'adhere': 0, 'adherence': 0, 'adherent': 0, 'adhering': 0, 'adhesion': 0, 'adhesive': 0, 'adieu': 0, 'adipose': 0, 'adjacency': 0, 'adjacent': 0, 'adjective': 0, 'adjoining': 0, 'adjourn': 0, 'adjournment': 0, 'adjudicate': 0, 'adjudication': 0, 'adjunct': 0, 'adjust': 0, 'adjustment': 0, 'adjuvant': 0, 'administer': 0, 'administration': 0, 'administrative': 0, 'admirable': 0, 'admiral': 0, 'admiralty': 0, 'admiration': 0, 'admire': 0, 'admirer': 0, 'admissibility': 0, 'admissible': 0, 'admission': 0, 'admit': 0, 'admittance': 0, 'admitted': 0, 'admitting': 0, 'admixture': 0, 'admonition': 0, 'ado': 0, 'adobe': 0, 'adolescence': 0, 'adolescent': 0, 'adopt': 0, 'adoption': 0, 'adorable': 0, 'adoration': 0, 'adore': 0, 'adorn': 0, 'adornment': 0, 'adrift': 1, 'adult': 0, 'adulterated': 0, 'adultery': 1, 'advance': 0, 'advanced': 0, 'advancement': 0, 'advancing': 0, 'advantage': 0, 'advantageous': 0, 'advent': 0, 'adventure': 0, 'adventurer': 0, 'adventurous': 0, 'adversary': 0, 'adverse': 1, 'adversity': 1, 'advertise': 0, 'advertisement': 0, 'advice': 0, 'advisable': 0, 'advise': 0, 'advised': 0, 'advisement': 0, 'adviser': 0, 'advocacy': 0, 'advocate': 0, 'aegis': 0, 'aeration': 0, 'aerial': 0, 'aerodrome': 0, 'aerodynamics': 0, 'aeronautics': 0, 'aeroplane': 0, 'aesthetic': 0, 'aesthetics': 0, 'aetiology': 0, 'afar': 0, 'affable': 0, 'affair': 0, 'affecting': 0, 'affection': 0, 'affections': 0, 'affiche': 0, 'affidavit': 0, 'affiliated': 0, 'affiliation': 0, 'affinity': 0, 'affirm': 0, 'affirmation': 0, 'affirmative': 0, 'affirmatively': 0, 'affix': 0, 'afflict': 1, 'afflicted': 0, 'affliction': 1, 'affluence': 0, 'affluent': 0, 'afford': 0, 'affront': 1, 'afield': 0, 'afore': 0, 'aforementioned': 0, 'aforesaid': 0, 'afraid': 0, 'afresh': 0, 'aft': 0, 'aftermath': 1, 'afternoon': 0, 'aftertaste': 0, 'afterthought': 0, 'aga': 0, 'agate': 0, 'age': 0, 'aged': 0, 'agency': 0, 'agent': 0, 'agglomeration': 0, 'aggravated': 0, 'aggravating': 1, 'aggravation': 0, 'aggregate': 0, 'aggregation': 0, 'aggression': 0, 'aggressive': 0, 'aggressor': 0, 'aghast': 0, 'agile': 0, 'agility': 0, 'agitated': 0, 'agitation': 0, 'agnostic': 0, 'ago': 0, 'agonizing': 0, 'agony': 1, 'agree': 0, 'agreeable': 0, 'agreed': 0, 'agreeing': 0, 'agreement': 0, 'agricultural': 0, 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'unattached': 0, 'unattainable': 1, 'unattended': 0, 'unattractive': 1, 'unauthorized': 0, 'unavoidable': 0, 'unaware': 0, 'unbalanced': 0, 'unbearable': 1, 'unbeaten': 1, 'unbelief': 0, 'unbelievable': 0, 'unbiased': 0, 'unborn': 0, 'unbound': 0, 'unbounded': 0, 'unbreakable': 0, 'unbridled': 0, 'unbroken': 0, 'uncanny': 0, 'uncaring': 1, 'uncertain': 0, 'uncertainty': 0, 'unchallenged': 0, 'unchangeable': 0, 'unchanged': 0, 'unclaimed': 0, 'uncle': 0, 'unclean': 0, 'uncomfortable': 0, 'uncommon': 0, 'uncommonly': 0, 'uncompromising': 0, 'unconcerned': 0, 'unconfirmed': 0, 'unconnected': 0, 'unconscionable': 0, 'unconscious': 0, 'unconsciousness': 0, 'unconstitutional': 0, 'unconstrained': 0, 'uncontested': 0, 'uncontrollable': 0, 'uncontrolled': 0, 'unconventional': 0, 'unconvinced': 0, 'uncooked': 0, 'uncorrelated': 0, 'uncover': 0, 'uncritical': 0, 'uncut': 0, 'undecided': 0, 'undefined': 0, 'undeniable': 0, 'undercover': 0, 'undercurrent': 0, 'underestimate': 0, 'undergo': 0, 'undergraduate': 0, 'underground': 0, 'underlie': 0, 'underline': 0, 'undermined': 0, 'underneath': 0, 'underpaid': 1, 'underpants': 0, 'underscore': 0, 'undersized': 0, 'understanding': 0, 'understood': 0, 'undertake': 0, 'undertaker': 1, 'undertaking': 0, 'underwood': 0, 'underwrite': 0, 'underwriter': 0, 'undeserved': 0, 'undesirable': 1, 'undesired': 1, 'undeveloped': 0, 'undirected': 0, 'undisclosed': 0, 'undiscovered': 0, 'undisputed': 0, 'undisturbed': 0, 'undivided': 0, 'undo': 0, 'undoing': 0, 'undoubted': 0, 'undress': 0, 'undressed': 0, 'undue': 0, 'undying': 1, 'unearned': 0, 'unearth': 0, 'uneasiness': 1, 'uneasy': 0, 'uneducated': 1, 'unemployed': 1, 'unencumbered': 0, 'unending': 0, 'unequal': 1, 'unequalled': 0, 'unequivocal': 0, 'unequivocally': 0, 'uneven': 0, 'uneventful': 0, 'unexpected': 0, 'unexpectedly': 0, 'unexplained': 1, 'unexplored': 0, 'unfailing': 0, 'unfair': 1, 'unfairness': 1, 'unfaithful': 0, 'unfamiliar': 0, 'unfavorable': 1, 'unfettered': 0, 'unfinished': 0, 'unflinching': 0, 'unfold': 0, 'unforeseen': 0, 'unforgiving': 1, 'unfortunate': 1, 'unfriendly': 1, 'unfulfilled': 1, 'unfurnished': 0, 'ungodly': 1, 'ungrateful': 0, 'unguarded': 0, 'unhappiness': 1, 'unhappy': 1, 'unharmed': 0, 'unhealthy': 1, 'unhindered': 0, 'unholy': 0, 'unicorn': 0, 'unification': 0, 'uniform': 0, 'uniformity': 0, 'uniformly': 0, 'unimaginable': 0, 'unimportant': 1, 'unimpressed': 0, 'unimproved': 0, 'uninfected': 0, 'uninformed': 0, 'uninhabited': 0, 'uninitiated': 0, 'uninspired': 1, 'unintelligible': 0, 'unintended': 0, 'unintentional': 0, 'unintentionally': 0, 'uninterested': 1, 'uninteresting': 1, 'uninterrupted': 0, 'uninvited': 1, 'union': 0, 'unique': 0, 'unison': 0, 'unit': 0, 'unitary': 0, 'unite': 0, 'united': 0, 'unity': 0, 'universal': 0, 'universality': 0, 'universe': 0, 'university': 0, 'unjust': 0, 'unjustifiable': 0, 'unjustified': 0, 'unkind': 1, 'unknowable': 0, 'unknown': 0, 'unlawful': 1, 'unleash': 0, 'unlicensed': 0, 'unlike': 0, 'unlimited': 0, 'unload': 0, 'unloaded': 0, 'unlock': 0, 'unlucky': 1, 'unmanageable': 0, 'unmarked': 0, 'unmarried': 0, 'unmask': 0, 'unmatched': 0, 'unmistakable': 0, 'unmitigated': 0, 'unmoved': 0, 'unnamed': 0, 'unnatural': 0, 'unnecessary': 0, 'unneeded': 0, 'unnoticed': 0, 'unnumbered': 0, 'unobserved': 0, 'unobstructed': 0, 'unobtrusive': 0, 'unoccupied': 0, 'unofficial': 0, 'unopened': 0, 'unopposed': 0, 'unordered': 0, 'unorganized': 0, 'unorthodox': 0, 'unpack': 0, 'unpaid': 1, 'unpleasant': 1, 'unpopular': 1, 'unprecedented': 0, 'unpredictable': 0, 'unprepared': 0, 'unpretentious': 0, 'unproductive': 0, 'unprofitable': 0, 'unprotected': 0, 'unproven': 0, 'unpublished': 1, 'unquestionable': 0, 'unquestionably': 0, 'unquestioned': 0, 'unread': 0, 'unreal': 0, 'unrealistic': 0, 'unrecorded': 0, 'unregistered': 0, 'unregulated': 0, 'unrelated': 0, 'unrelenting': 0, 'unreliable': 0, 'unrepentant': 0, 'unrequited': 1, 'unresolved': 0, 'unrest': 1, 'unrestrained': 0, 'unrestricted': 0, 'unruly': 0, 'unsafe': 0, 'unsatisfactory': 0, 'unsatisfied': 1, 'unsavory': 0, 'unscathed': 0, 'unscientific': 0, 'unscrupulous': 0, 'unseat': 1, 'unseen': 0, 'unselfish': 0, 'unsettled': 0, 'unsightly': 0, 'unsophisticated': 0, 'unspeakable': 0, 'unspecified': 0, 'unstable': 0, 'unsteady': 0, 'unsuccessful': 1, 'unsuitable': 0, 'unsung': 0, 'unsupported': 0, 'unsurpassed': 0, 'unsuspecting': 0, 'unsustainable': 0, 'unsweetened': 0, 'unsympathetic': 0, 'untamed': 0, 'untenable': 0, 'untested': 0, 'unthinkable': 0, 'untidy': 0, 'untie': 0, 'untimely': 0, 'untitled': 1, 'untold': 0, 'untouched': 0, 'untoward': 0, 'untrained': 0, 'untranslated': 0, 'untrue': 0, 'untrustworthy': 0, 'unused': 0, 'unusual': 0, 'unusually': 0, 'unveil': 0, 'unveiling': 0, 'unverified': 0, 'unwarranted': 0, 'unwary': 0, 'unwashed': 0, 'unwavering': 0, 'unwelcome': 1, 'unwell': 1, 'unwilling': 0, 'unwillingly': 0, 'unwillingness': 0, 'unwind': 0, 'unwise': 0, 'unwitting': 0, 'unwittingly': 0, 'unworthy': 0, 'unwritten': 0, 'unyielding': 0, 'upheaval': 1, 'uphill': 0, 'upholstery': 0, 'upland': 0, 'uplands': 0, 'uplift': 0, 'upper': 0, 'upright': 0, 'uprising': 0, 'uproar': 0, 'upset': 1, 'upshot': 0, 'upstairs': 0, 'upstart': 0, 'upwards': 0, 'uranium': 0, 'urban': 0, 'urchin': 0, 'urge': 0, 'urgency': 0, 'urgent': 0, 'urinalysis': 0, 'urn': 1, 'usage': 0, 'usefully': 0, 'usefulness': 0, 'useless': 0, 'usher': 0, 'usual': 0, 'usurp': 0, 'usurped': 0, 'usury': 0, 'utensil': 0, 'utilitarian': 0, 'utility': 0, 'utilization': 0, 'utilize': 0, 'utmost': 0, 'utopian': 0, 'utterance': 0, 'utterly': 0, 'vacancy': 0, 'vacation': 0, 'vaccination': 0, 'vaccine': 0, 'vacuolar': 0, 'vacuole': 0, 'vacuous': 0, 'vacuum': 0, 'vague': 0, 'vagueness': 0, 'vainly': 1, 'valance': 0, 'vale': 0, 'valet': 0, 'valiant': 0, 'validity': 0, 'valley': 0, 'valor': 0, 'valuable': 0, 'valuation': 0, 'valve': 0, 'vamp': 0, 'vampire': 0, 'van': 0, 'vane': 0, 'vanguard': 0, 'vanilla': 0, 'vanish': 0, 'vanished': 1, 'vanity': 0, 'vanquish': 0, 'vapor': 0, 'vara': 0, 'variable': 0, 'variance': 0, 'variation': 0, 'variations': 0, 'varicella': 1, 'varicose': 0, 'varied': 0, 'variegated': 0, 'variety': 0, 'vary': 0, 'vascular': 0, 'vase': 0, 'vast': 0, 'vat': 0, 'vaudeville': 0, 'vault': 0, 'vaulted': 0, 'vaulting': 0, 'veal': 1, 'vector': 0, 'veer': 0, 'vega': 0, 'vegetable': 0, 'vegetarian': 0, 'vegetarianism': 0, 'vegetation': 0, 'vegetative': 1, 'vehement': 0, 'vehicle': 0, 'veil': 0, 'veiled': 0, 'vein': 0, 'veined': 0, 'vellum': 0, 'velocity': 0, 'velour': 0, 'velvet': 0, 'velvety': 0, 'vena': 0, 'vendetta': 1, 'vendor': 0, 'veneer': 0, 'venerable': 0, 'veneration': 0, 'vengeance': 0, 'vengeful': 0, 'venison': 0, 'venom': 0, 'venomous': 0, 'venous': 0, 'vent': 0, 'ventilation': 0, 'ventilator': 0, 'ventricle': 0, 'ventricular': 0, 'venture': 0, 'venue': 0, 'veracity': 0, 'veranda': 0, 'verbal': 0, 'verbatim': 0, 'verbiage': 0, 'verbose': 0, 'verbosity': 0, 'verdant': 0, 'verdict': 0, 'verge': 0, 'verification': 0, 'verified': 0, 'verify': 0, 'verily': 0, 'veritable': 0, 'vermin': 0, 'vernacular': 0, 'vernal': 0, 'veronica': 0, 'versatile': 0, 'versatility': 0, 'verse': 0, 'version': 0, 'versus': 0, 'vert': 0, 'vertebra': 0, 'vertebral': 0, 'vertex': 0, 'vertical': 0, 'vertically': 0, 'vertigo': 0, 'verve': 0, 'vesicle': 0, 'vesicular': 0, 'vessel': 0, 'vest': 0, 'vested': 0, 'vestibule': 0, 'vestige': 0, 'vet': 0, 'veteran': 0, 'veterinarian': 0, 'veto': 0, 'viability': 0, 'viable': 0, 'viaduct': 0, 'vial': 0, 'vibrate': 0, 'vibration': 0, 'vibratory': 0, 'vicar': 0, 'vicarious': 0, 'vice': 0, 'vicinity': 0, 'vicious': 0, 'victim': 1, 'victimized': 1, 'victor': 0, 'victoria': 0, 'victorious': 0, 'victory': 0, 'videotape': 0, 'vie': 0, 'view': 0, 'vigil': 0, 'vigilance': 0, 'vigilant': 0, 'vignette': 0, 'vigor': 0, 'vigorous': 0, 'viking': 0, 'villa': 0, 'village': 0, 'villager': 0, 'villain': 0, 'villainous': 0, 'vinaigrette': 0, 'vindicate': 0, 'vindicated': 0, 'vindication': 0, 'vindictive': 0, 'vinegar': 0, 'vineyard': 0, 'viola': 0, 'violation': 1, 'violence': 1, 'violent': 0, 'violently': 1, 'violet': 0, 'violin': 0, 'violinist': 0, 'viper': 0, 'virgin': 0, 'virginity': 0, 'virology': 0, 'virtual': 0, 'virtually': 0, 'virtue': 0, 'virtuoso': 0, 'virtuous': 0, 'virulence': 0, 'virus': 0, 'visa': 0, 'visage': 0, 'viscosity': 0, 'viscous': 0, 'vise': 0, 'visibility': 0, 'visible': 0, 'visibly': 0, 'vision': 0, 'visionary': 0, 'visit': 0, 'visitation': 0, 'visiting': 0, 'visitor': 0, 'visor': 0, 'vista': 0, 'visual': 0, 'visualize': 0, 'vital': 0, 'vitality': 0, 'vitreous': 0, 'vivacious': 0, 'vivid': 0, 'vixen': 0, 'vocabulary': 0, 'vocal': 0, 'vocalist': 0, 'vocation': 0, 'vogue': 0, 'voice': 0, 'voiceless': 0, 'void': 0, 'volatility': 0, 'volcanic': 0, 'volcano': 0, 'volition': 0, 'volley': 0, 'voltmeter': 0, 'volume': 0, 'voluminous': 0, 'voluntarily': 0, 'voluntary': 0, 'volunteer': 0, 'volunteering': 0, 'volunteers': 0, 'voluptuous': 0, 'vomit': 0, 'vomiting': 0, 'voodoo': 0, 'voracious': 0, 'vortex': 0, 'vote': 1, 'voting': 0, 'votive': 0, 'vouch': 0, 'voucher': 0, 'vow': 0, 'vowel': 0, 'voyage': 0, 'voyager': 0, 'vulgar': 0, 'vulgarity': 1, 'vulnerability': 1, 'vulnerable': 0, 'vulture': 0, 'wad': 0, 'wade': 0, 'wafer': 0, 'waffle': 1, 'wag': 0, 'wager': 0, 'wages': 0, 'wagon': 0, 'wail': 1, 'waist': 0, 'waistcoat': 0, 'wait': 0, 'waiter': 0, 'waiting': 0, 'waive': 0, 'wake': 0, 'walk': 0, 'walker': 0, 'wall': 0, 'wallet': 0, 'wallow': 1, 'walnut': 0, 'waltz': 0, 'wan': 1, 'wand': 0, 'wander': 0, 'wanderer': 0, 'wandering': 0, 'wane': 1, 'waning': 0, 'wanting': 1, 'war': 0, 'warbler': 0, 'ward': 0, 'warden': 0, 'wardrobe': 0, 'ware': 0, 'warehouse': 0, 'warfare': 1, 'warlike': 0, 'warlock': 0, 'warming': 0, 'warn': 0, 'warned': 0, 'warning': 0, 'warp': 1, 'warped': 0, 'warrant': 0, 'warranted': 0, 'warrants': 0, 'warranty': 0, 'warren': 0, 'warrior': 0, 'wart': 0, 'wary': 0, 'wash': 0, 'washing': 0, 'washout': 0, 'wasp': 0, 'waste': 0, 'wasted': 0, 'wasteful': 1, 'wasting': 1, 'watch': 0, 'watchdog': 0, 'watchful': 0, 'watchman': 0, 'water': 0, 'watercourse': 0, 'watered': 0, 'waterproof': 0, 'waterworks': 0, 'watery': 0, 'wave': 0, 'waver': 0, 'wavering': 0, 'waves': 0, 'wavy': 0, 'wax': 0, 'waxy': 0, 'ways': 0, 'wayward': 0, 'weakened': 0, 'weakly': 1, 'weakness': 0, 'wealth': 0, 'wealthy': 0, 'weapon': 0, 'wear': 0, 'wearily': 1, 'weariness': 1, 'wearing': 0, 'weary': 1, 'weather': 0, 'weathered': 0, 'weatherproof': 0, 'weave': 0, 'web': 0, 'wed': 0, 'wedded': 0, 'wedge': 0, 'wee': 0, 'weed': 0, 'weeding': 0, 'weeds': 1, 'weedy': 0, 'week': 0, 'weekly': 0, 'weep': 1, 'weeping': 1, 'weigh': 0, 'weighing': 0, 'weight': 1, 'weightless': 0, 'weights': 0, 'weighty': 0, 'weir': 0, 'weird': 0, 'weirdo': 0, 'welcomed': 0, 'weld': 0, 'welfare': 0, 'wellhead': 0, 'welt': 0, 'wen': 0, 'wench': 0, 'western': 0, 'wet': 0, 'whack': 0, 'whale': 0, 'wham': 0, 'wharf': 0, 'whatsoever': 0, 'wheel': 0, 'wheels': 0, 'whereabouts': 0, 'wherefore': 0, 'wherewith': 0, 'wherewithal': 0, 'whet': 0, 'whiff': 0, 'whilst': 0, 'whim': 0, 'whimper': 1, 'whimsical': 0, 'whimsy': 0, 'whine': 1, 'whip': 0, 'whirl': 0, 'whirlpool': 0, 'whirlwind': 0, 'whisk': 0, 'whisker': 0, 'whisky': 0, 'whisper': 0, 'whispered': 0, 'whistle': 0, 'whit': 0, 'white': 0, 'whiteness': 0, 'whitish': 0, 'whiz': 0, 'wholesome': 0, 'wholly': 0, 'whoop': 0, 'whopping': 0, 'whore': 0, 'wick': 0, 'wicked': 0, 'wickedness': 0, 'wicker': 0, 'wicket': 0, 'wide': 0, 'widely': 0, 'widen': 0, 'widespread': 0, 'widow': 1, 'widower': 1, 'width': 0, 'wield': 0, 'wife': 0, 'wig': 0, 'wight': 0, 'wild': 0, 'wildcat': 0, 'wilderness': 1, 'wildfire': 1, 'willful': 1, 'willingly': 0, 'willingness': 0, 'willow': 0, 'wilted': 0, 'wily': 0, 'wimp': 0, 'wimpy': 1, 'wince': 1, 'winch': 0, 'wind': 0, 'windfall': 0, 'winding': 0, 'windmill': 0, 'window': 0, 'windy': 0, 'wine': 0, 'wing': 0, 'winged': 0, 'wink': 0, 'winner': 0, 'winning': 1, 'winnings': 0, 'winter': 0, 'wintry': 0, 'wipe': 0, 'wire': 0, 'wireless': 0, 'wis': 0, 'wisdom': 0, 'wise': 0, 'wishful': 0, 'wistful': 0, 'wit': 0, 'witch': 0, 'witchcraft': 1, 'withal': 0, 'withdraw': 1, 'withdrawal': 0, 'wither': 1, 'withered': 0, 'withstand': 0, 'witness': 0, 'wits': 0, 'witty': 0, 'wizard': 0, 'woe': 1, 'woeful': 1, 'woefully': 1, 'woman': 0, 'womanhood': 0, 'womanly': 0, 'womb': 0, 'wonderful': 0, 'wonderfully': 0, 'wondrous': 0, 'wont': 0, 'woo': 0, 'wood': 0, 'woodcut': 0, 'wooden': 0, 'woodlands': 0, 'woody': 0, 'wooing': 0, 'wool': 0, 'woolly': 0, 'wop': 0, 'word': 0, 'wording': 0, 'words': 0, 'wordy': 0, 'work': 0, 'workbook': 0, 'worker': 0, 'working': 0, 'workman': 0, 'workmanship': 0, 'workplace': 0, 'works': 0, 'workshop': 0, 'world': 0, 'worldly': 0, 'worldwide': 0, 'worm': 0, 'worn': 1, 'worried': 1, 'worry': 1, 'worrying': 1, 'worse': 1, 'worsening': 1, 'worship': 0, 'worth': 0, 'worthless': 1, 'worthy': 0, 'wot': 0, 'wound': 1, 'wrangler': 0, 'wrangling': 1, 'wrap': 0, 'wrapper': 0, 'wrapping': 0, 'wrath': 0, 'wreak': 0, 'wreath': 0, 'wreck': 1, 'wrecked': 1, 'wrench': 0, 'wrest': 0, 'wrestle': 0, 'wrestler': 0, 'wrestling': 0, 'wretch': 1, 'wretched': 1, 'wright': 0, 'wring': 0, 'wrinkle': 0, 'wrinkled': 1, 'wrist': 0, 'wristband': 0, 'wristwatch': 0, 'writ': 0, 'write': 0, 'writer': 0, 'writing': 0, 'written': 0, 'wrong': 0, 'wrongdoing': 1, 'wrongful': 1, 'wrongly': 1, 'wrought': 0, 'wry': 0, 'xenophobia': 0, 'xerox': 0, 'yacht': 0, 'yachting': 0, 'yak': 0, 'yam': 0, 'yank': 0, 'yard': 0, 'yarn': 0, 'yaw': 0, 'yawn': 0, 'yawning': 0, 'yea': 0, 'year': 0, 'yearbook': 0, 'yearling': 0, 'yearly': 0, 'yearn': 0, 'yearning': 0, 'years': 0, 'yeast': 0, 'yell': 0, 'yellow': 0, 'yellows': 0, 'yelp': 0, 'yeoman': 0, 'yesterday': 0, 'yesteryear': 0, 'yew': 0, 'yield': 0, 'yielding': 0, 'yogi': 0, 'yoke': 0, 'yolk': 0, 'yon': 0, 'yonder': 0, 'young': 0, 'younger': 0, 'youth': 0, 'zany': 0, 'zap': 0, 'zeal': 0, 'zealot': 0, 'zealous': 0, 'zebra': 0, 'zenith': 0, 'zephyr': 0, 'zeppelin': 0, 'zest': 0, 'zip': 0, 'zodiac': 0, 'zone': 0, 'zoo': 0, 'zoological': 0, 'zoology': 0, 'zoom': 0}
#For each record
#For each word in record
#Get the word score (score is a number if the word is in Lexicon, 0 if not)
#Add all the scores and find the ploarity
sadnessnrc = []
strength =[]
for record in corpus:
#print("record", record)
score = 0
words = record.replace("'","").lower().split()
for word in words:
#print("word", word)
if word in (lexicons):
score = score + lexicons[word]
#print("score",score)
strength.append(score)
#print('strength',strength)
if (score > 0):
sadnessnrc.append('1')
else:
sadnessnrc.append('0')
#else:
# prediction.append('neutral')
print(sadnessnrc)
#print(prediction)
['1', '0', '0', '0', '1', '0', '1', '1', '0', '1', '0', '0', '0', '1', '0', '1', '1', '0', '1', '0', '0', '1', '0', '1', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '1', '0', '0', '1', '0', '1', '0', '0', '0', '0', '0', '1', '0', '1', '0', '1', '0', '0', '0', '1', '1', '0', '0', '0', '1', '0', '1', '1', '0', '0', '0', '0', '0', '0', '1', '1', '1', '0', '0', '0', '0', '1', '1', '1', '0', '0', '0', '1', '1', '1', '0', '0', '0', '1', '1', '1', '1', '0', '1', '1', '1', '0', '0', '1', '0', '0', '1', '0', '0', '1', '1', '0', '1', '0', '0', '1', '1', '0', '1', '0', '0', '1', '0', '1', '1', '1', '0', '1', '0', '0', '1', '0', '0', '1', '0', '1', '1', '0', '1', '1', '0', '1', '0', '0', '0', '1', '0', '1', '1', '1', '1', '1', '0', '1', '1', '0', '1', '1', '0', '0', '0', '1', '0', '0', '1', '1', '0', '0', '0', '0', '1', '0', '0', '0', '1', '0', '0', '0', '0', '1', '1', '0', '0', '1', '1', '0', '0', '1', '0', '1', '1', '0', '0', '0', '1', '0', '0', '0', '1', '0', '0', '0', '1', '1', '1', '1', '1', '0', '1', '0', '0', '1', '0', '0', '1', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '1', '1', '0', '1', '0', '0', '0', '0', '1', '1', '0', '1', '1', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '1', '0', '0', '1', '0', '0', '1', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '1', '0', '1', '0', '0', '0', '1', '0', '1', '1', '0', '0', '1', '0', '0', '0', '0', '1', '1', '1', '0', '1', '0', '1', '0', '1', '1', '1', '0', '1', '0', '1', '0', '0', '1', '1', '1', '0', '0', '1', '0', '0', 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df_new['sadnessnrc']= sadnessnrc
df_new.head()
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | tokenized_docs_no_stopwords | preprocessed_docs | word_final | strength_affin | prediction_affin | positivenrc | negativenrc | angernrc | anticipationnrc | disgustnrc | fearnrc | joynrc | sadnessnrc | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | case id worst poor customer service giving res... | -2 | negative | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 1 |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | ['please', 'dont', 'install', 'this', 'app', '... | ['please', 'dont', 'install', 'app', 'people',... | ['please', 'dont', 'install', 'app', 'people',... | please dont install app people stole informati... | -3 | negative | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... | ['dont', 'waste', 'your', 'time', 'and', 'mone... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | dont waste time money woohoo payment successfu... | 9 | positive | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 0 |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | worst customer supportthey wont pick call wont... | -5 | negative | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... | ['was', 'a', 'happy', 'customer', 'till', 'i',... | ['happy', 'customer', 'till', 'faced', 'error'... | ['happy', 'customer', 'till', 'faced', 'error'... | happy customer till faced error guess even don... | 0 | neutral | 1 | 1 | 0 | 1 | 0 | 0 | 1 | 1 |
#Read the lexicon file
lex_file = open("D:\\11 Project\\Project\\NRC_file - Surprise.csv")
lexicons = {}
records = lex_file.readlines()
for record in records:
#print(record) # line contains newline charecter
#print(record.rstrip('\n').split(",")) - to remove new line charecter
lexicons[record.rstrip('\n').split(",")[0]] = int(record.rstrip('\n').split(",")[1])
print(lexicons)
{'aback': 0, 'abacus': 0, 'abandon': 0, 'abandoned': 0, 'abandonment': 1, 'abate': 0, 'abatement': 0, 'abba': 0, 'abbot': 0, 'abbreviate': 0, 'abbreviation': 0, 'abdomen': 0, 'abdominal': 0, 'abduction': 1, 'aberrant': 0, 'aberration': 0, 'abeyance': 0, 'abhor': 0, 'abhorrent': 0, 'abide': 0, 'ability': 0, 'abject': 0, 'ablation': 0, 'ablaze': 0, 'abnormal': 0, 'aboard': 0, 'abode': 0, 'abolish': 0, 'abolition': 0, 'abominable': 0, 'abomination': 0, 'aboriginal': 0, 'abort': 0, 'abortion': 0, 'abortive': 0, 'abound': 0, 'abovementioned': 0, 'abrasion': 0, 'abroad': 0, 'abrogate': 0, 'abrupt': 1, 'abruptly': 0, 'abscess': 0, 'absence': 0, 'absent': 0, 'absentee': 0, 'absenteeism': 0, 'absinthe': 0, 'absolute': 0, 'absolution': 0, 'absorbed': 0, 'absorbent': 0, 'absorbing': 0, 'absorption': 0, 'abstain': 0, 'abstention': 0, 'abstinence': 0, 'abstract': 0, 'abstraction': 0, 'absurd': 0, 'absurdity': 0, 'abundance': 0, 'abundant': 0, 'abuse': 0, 'abutment': 0, 'aby': 0, 'abysmal': 0, 'abyss': 0, 'academic': 0, 'academy': 0, 'accede': 0, 'accelerate': 0, 'acceleration': 0, 'accent': 0, 'accentuate': 0, 'accept': 0, 'acceptable': 0, 'acceptance': 0, 'access': 0, 'accessible': 0, 'accession': 0, 'accessory': 0, 'accident': 1, 'accidental': 1, 'accidentally': 1, 'accolade': 1, 'accommodate': 0, 'accommodation': 0, 'accompaniment': 0, 'accompany': 0, 'accompanying': 0, 'accomplice': 0, 'accomplish': 0, 'accomplished': 0, 'accomplishment': 0, 'accord': 0, 'accordance': 0, 'accordion': 0, 'account': 0, 'accountability': 0, 'accountable': 0, 'accountant': 0, 'accounting': 0, 'accounts': 0, 'accredited': 0, 'accretion': 0, 'accrue': 0, 'accueil': 0, 'accumulate': 0, 'accumulation': 0, 'accuracy': 0, 'accurate': 0, 'accursed': 0, 'accusation': 0, 'accusative': 0, 'accused': 0, 'accuser': 0, 'accusing': 0, 'accustomed': 0, 'ace': 0, 'acetic': 0, 'ache': 0, 'achieve': 0, 'achievement': 0, 'aching': 0, 'acid': 0, 'acidity': 0, 'acknowledge': 0, 'acknowledged': 0, 'acknowledgment': 0, 'acme': 0, 'acoustic': 0, 'acoustics': 0, 'acquaint': 0, 'acquaintance': 0, 'acquainted': 0, 'acquiescence': 0, 'acquire': 0, 'acquiring': 0, 'acquisition': 0, 'acquisitions': 0, 'acreage': 0, 'acres': 0, 'acrobat': 0, 'act': 0, 'acting': 0, 'action': 0, 'actionable': 0, 'active': 0, 'activity': 0, 'actor': 0, 'actual': 0, 'actuality': 0, 'actuary': 0, 'acuity': 0, 'acumen': 0, 'acupuncture': 0, 'acutely': 0, 'adage': 0, 'adamant': 0, 'adapt': 0, 'adaptable': 0, 'add': 0, 'added': 0, 'addendum': 0, 'adder': 0, 'addiction': 0, 'addition': 0, 'additional': 0, 'additive': 0, 'address': 0, 'addressee': 0, 'addresses': 0, 'adept': 0, 'adequacy': 0, 'adequate': 0, 'adhere': 0, 'adherence': 0, 'adherent': 0, 'adhering': 0, 'adhesion': 0, 'adhesive': 0, 'adieu': 0, 'adipose': 0, 'adjacency': 0, 'adjacent': 0, 'adjective': 0, 'adjoining': 0, 'adjourn': 0, 'adjournment': 0, 'adjudicate': 0, 'adjudication': 0, 'adjunct': 0, 'adjust': 0, 'adjustment': 0, 'adjuvant': 0, 'administer': 0, 'administration': 0, 'administrative': 0, 'admirable': 0, 'admiral': 0, 'admiralty': 0, 'admiration': 0, 'admire': 0, 'admirer': 0, 'admissibility': 0, 'admissible': 0, 'admission': 0, 'admit': 0, 'admittance': 0, 'admitted': 0, 'admitting': 0, 'admixture': 0, 'admonition': 0, 'ado': 0, 'adobe': 0, 'adolescence': 0, 'adolescent': 0, 'adopt': 0, 'adoption': 0, 'adorable': 0, 'adoration': 0, 'adore': 0, 'adorn': 0, 'adornment': 0, 'adrift': 0, 'adult': 0, 'adulterated': 0, 'adultery': 0, 'advance': 1, 'advanced': 0, 'advancement': 0, 'advancing': 0, 'advantage': 0, 'advantageous': 0, 'advent': 0, 'adventure': 0, 'adventurer': 0, 'adventurous': 0, 'adversary': 0, 'adverse': 0, 'adversity': 0, 'advertise': 0, 'advertisement': 0, 'advice': 0, 'advisable': 0, 'advise': 0, 'advised': 0, 'advisement': 0, 'adviser': 0, 'advocacy': 0, 'advocate': 0, 'aegis': 0, 'aeration': 0, 'aerial': 0, 'aerodrome': 0, 'aerodynamics': 0, 'aeronautics': 0, 'aeroplane': 0, 'aesthetic': 0, 'aesthetics': 0, 'aetiology': 0, 'afar': 0, 'affable': 0, 'affair': 0, 'affecting': 0, 'affection': 0, 'affections': 0, 'affiche': 0, 'affidavit': 0, 'affiliated': 0, 'affiliation': 0, 'affinity': 0, 'affirm': 0, 'affirmation': 0, 'affirmative': 0, 'affirmatively': 0, 'affix': 0, 'afflict': 0, 'afflicted': 0, 'affliction': 0, 'affluence': 0, 'affluent': 0, 'afford': 0, 'affront': 1, 'afield': 0, 'afore': 0, 'aforementioned': 0, 'aforesaid': 0, 'afraid': 0, 'afresh': 0, 'aft': 0, 'aftermath': 0, 'afternoon': 0, 'aftertaste': 0, 'afterthought': 0, 'aga': 0, 'agate': 0, 'age': 0, 'aged': 0, 'agency': 0, 'agent': 0, 'agglomeration': 0, 'aggravated': 0, 'aggravating': 0, 'aggravation': 0, 'aggregate': 0, 'aggregation': 0, 'aggression': 0, 'aggressive': 0, 'aggressor': 0, 'aghast': 1, 'agile': 0, 'agility': 0, 'agitated': 0, 'agitation': 0, 'agnostic': 0, 'ago': 0, 'agonizing': 0, 'agony': 0, 'agree': 0, 'agreeable': 0, 'agreed': 0, 'agreeing': 0, 'agreement': 0, 'agricultural': 0, 'agriculture': 0, 'aground': 0, 'agua': 0, 'ahead': 0, 'aid': 0, 'aiding': 0, 'ail': 0, 'ailing': 0, 'ailment': 0, 'aim': 0, 'aimless': 0, 'air': 0, 'airbag': 0, 'airlift': 0, 'airline': 0, 'airman': 0, 'airplane': 0, 'airport': 0, 'airs': 0, 'airship': 0, 'aisle': 0, 'ait': 0, 'ajar': 0, 'akin': 0, 'alabaster': 0, 'alarm': 1, 'alarming': 1, 'alb': 0, 'album': 0, 'alchemy': 0, 'alcohol': 0, 'alcoholism': 0, 'alcove': 0, 'alert': 0, 'alertness': 1, 'alerts': 1, 'alfalfa': 0, 'algebra': 0, 'algebraic': 0, 'algorithm': 0, 'alibi': 0, 'alien': 0, 'alienate': 0, 'alienated': 0, 'alienation': 0, 'alight': 0, 'aligned': 0, 'alignment': 0, 'alike': 0, 'alimentation': 0, 'alimony': 0, 'aliquot': 0, 'alive': 0, 'alkali': 0, 'alkaloids': 0, 'allay': 0, 'allegation': 0, 'allege': 0, 'alleged': 0, 'allegiance': 0, 'allegorical': 0, 'allegory': 0, 'allegro': 0, 'alleviate': 0, 'alleviation': 0, 'alley': 0, 'alliance': 0, 'allied': 0, 'alligator': 0, 'allocate': 0, 'allocation': 0, 'allot': 0, 'allotment': 0, 'allowable': 0, 'allowance': 0, 'allowed': 0, 'alloy': 0, 'allure': 1, 'alluring': 0, 'allusion': 0, 'alluvial': 0, 'ally': 0, 'almanac': 0, 'almighty': 0, 'aloft': 0, 'aloha': 0, 'alongside': 0, 'aloof': 0, 'aloud': 0, 'alphabet': 0, 'alphabetical': 0, 'altar': 0, 'alter': 0, 'alteration': 0, 'altercation': 0, 'altered': 0, 'alternate': 0, 'alternative': 0, 'altitude': 0, 'alto': 0, 'altogether': 0, 'alumnus': 0, 'alveolar': 0, 'amalgam': 0, 'amalgamation': 0, 'amass': 0, 'amateur': 0, 'amaze': 1, 'amazement': 0, 'amazingly': 1, 'ambassador': 0, 'amber': 0, 'ambient': 0, 'ambiguity': 0, 'ambiguous': 0, 'ambit': 0, 'ambition': 0, 'ambitious': 0, 'ambulance': 0, 'ambush': 1, 'ameliorate': 0, 'amen': 0, 'amenable': 0, 'amend': 0, 'amendment': 0, 'amends': 0, 'amenity': 0, 'amethyst': 0, 'amiable': 0, 'amicable': 0, 'amid': 0, 'amidst': 0, 'ammonia': 0, 'ammunition': 0, 'amnesia': 0, 'amnesty': 0, 'amorphous': 0, 'amortization': 0, 'amount': 0, 'amour': 0, 'ampersand': 0, 'amphetamines': 0, 'amphibian': 0, 'amphibious': 0, 'amphitheater': 0, 'amplification': 0, 'amplify': 0, 'amplitude': 0, 'amply': 0, 'amputation': 0, 'amulet': 0, 'amuse': 0, 'amused': 0, 'amusement': 0, 'amusing': 0, 'ana': 0, 'anaconda': 0, 'anaesthesia': 0, 'anaesthetic': 0, 'anal': 0, 'analgesic': 0, 'analogous': 0, 'analogue': 0, 'analogy': 0, 'analysis': 0, 'analyst': 0, 'analytic': 0, 'analyze': 0, 'analyzer': 0, 'anarchism': 0, 'anarchist': 0, 'anarchy': 0, 'anastomosis': 0, 'anathema': 0, 'anatomic': 0, 'anatomy': 0, 'ancestor': 0, 'ancestral': 0, 'ancestry': 0, 'anchor': 0, 'anchorage': 0, 'ancient': 0, 'ancillary': 0, 'androgen': 0, 'anemone': 0, 'anew': 0, 'angel': 1, 'angelic': 0, 'anger': 0, 'angina': 0, 'angiography': 0, 'angle': 0, 'angling': 0, 'angry': 0, 'anguish': 0, 'angular': 0, 'anhydrous': 0, 'animal': 0, 'animate': 0, 'animated': 0, 'animation': 0, 'animosity': 0, 'animus': 0, 'ankle': 0, 'annals': 0, 'annex': 0, 'annexation': 0, 'annexe': 0, 'annihilate': 0, 'annihilated': 0, 'annihilation': 0, 'annotate': 0, 'annotation': 0, 'announce': 0, 'announcement': 0, 'annoy': 0, 'annoyance': 0, 'annoying': 0, 'annuity': 0, 'annul': 0, 'annular': 0, 'annulment': 0, 'annulus': 0, 'anointing': 0, 'anomalous': 0, 'anomaly': 1, 'anon': 0, 'anonymous': 0, 'answer': 0, 'answerable': 0, 'answering': 0, 'ant': 0, 'antagonism': 0, 'antagonist': 0, 'antagonistic': 0, 'ante': 0, 'antecedent': 0, 'antelope': 0, 'antenna': 0, 'anterior': 0, 'anthem': 0, 'anthology': 0, 'anthrax': 0, 'anthropology': 0, 'antibiotic': 0, 'antibiotics': 0, 'antichrist': 0, 'anticipation': 0, 'anticipatory': 0, 'antidote': 0, 'antifungal': 0, 'antimony': 0, 'antipathy': 0, 'antiquarian': 0, 'antiquated': 0, 'antique': 0, 'antiquity': 0, 'antiseptic': 0, 'antisocial': 0, 'antithesis': 0, 'antithetical': 0, 'antiviral': 0, 'antler': 0, 'anvil': 0, 'anxiety': 0, 'anxious': 0, 'aorta': 0, 'apace': 0, 'apache': 0, 'apartment': 0, 'apathetic': 0, 'apathy': 0, 'ape': 0, 'aperture': 0, 'apex': 0, 'aphid': 0, 'apiece': 0, 'aplomb': 0, 'apocalyptic': 0, 'apologetic': 0, 'apologist': 0, 'apologize': 0, 'apology': 0, 'apostasy': 0, 'apostate': 0, 'apostle': 0, 'apostolic': 0, 'apostrophe': 0, 'appalling': 0, 'apparatus': 0, 'apparel': 0, 'apparently': 0, 'apparition': 1, 'appeal': 0, 'appearance': 0, 'appease': 0, 'appellant': 0, 'append': 0, 'appendage': 0, 'appendicitis': 0, 'appendix': 0, 'appetite': 0, 'appetizer': 0, 'applause': 1, 'apple': 0, 'appliance': 0, 'appliances': 0, 'applicability': 0, 'applicable': 0, 'applicant': 0, 'application': 0, 'apply': 0, 'appoint': 0, 'appointment': 0, 'appointments': 0, 'apportion': 0, 'apportionment': 0, 'appraise': 0, 'appreciable': 0, 'appreciation': 0, 'apprehend': 0, 'apprehension': 0, 'apprehensive': 0, 'apprentice': 0, 'apprenticeship': 0, 'approach': 0, 'approaching': 0, 'approbation': 0, 'appropriation': 0, 'approval': 0, 'approve': 0, 'approving': 0, 'approximate': 0, 'approximately': 0, 'approximating': 0, 'approximation': 0, 'appurtenances': 0, 'apron': 0, 'apt': 0, 'aptitude': 0, 'aqua': 0, 'aquamarine': 0, 'aquarium': 0, 'aquatic': 0, 'aqueduct': 0, 'aqueous': 0, 'arable': 0, 'arbiter': 0, 'arbitrate': 0, 'arbitration': 0, 'arbitrator': 0, 'arbor': 0, 'arc': 0, 'arcade': 0, 'arch': 0, 'archaeological': 0, 'archaeologist': 0, 'archaeology': 0, 'archaic': 0, 'archbishop': 0, 'arched': 0, 'archer': 0, 'archery': 0, 'archetype': 0, 'archipelago': 0, 'architect': 0, 'architecture': 0, 'archive': 0, 'arctic': 0, 'ardent': 0, 'ardor': 0, 'arduous': 0, 'area': 0, 'arena': 0, 'areola': 0, 'argent': 0, 'argue': 0, 'argument': 0, 'argumentation': 0, 'argumentative': 0, 'arguments': 0, 'arid': 0, 'aristocracy': 0, 'aristocrat': 0, 'aristocratic': 0, 'arithmetic': 0, 'ark': 0, 'arm': 0, 'armada': 0, 'armament': 0, 'armaments': 0, 'armature': 0, 'armed': 0, 'armor': 0, 'armored': 0, 'armory': 0, 'arms': 0, 'army': 0, 'aroma': 0, 'arousal': 0, 'arouse': 0, 'arraignment': 0, 'arrange': 0, 'arranged': 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'vanished': 1, 'vanity': 0, 'vanquish': 0, 'vapor': 0, 'vara': 0, 'variable': 1, 'variance': 0, 'variation': 0, 'variations': 0, 'varicella': 0, 'varicose': 0, 'varied': 0, 'variegated': 0, 'variety': 0, 'vary': 0, 'vascular': 0, 'vase': 0, 'vast': 0, 'vat': 0, 'vaudeville': 0, 'vault': 0, 'vaulted': 0, 'vaulting': 0, 'veal': 0, 'vector': 0, 'veer': 1, 'vega': 0, 'vegetable': 0, 'vegetarian': 0, 'vegetarianism': 0, 'vegetation': 0, 'vegetative': 0, 'vehement': 0, 'vehicle': 0, 'veil': 0, 'veiled': 0, 'vein': 0, 'veined': 0, 'vellum': 0, 'velocity': 0, 'velour': 0, 'velvet': 0, 'velvety': 0, 'vena': 0, 'vendetta': 0, 'vendor': 0, 'veneer': 0, 'venerable': 0, 'veneration': 0, 'vengeance': 0, 'vengeful': 0, 'venison': 0, 'venom': 0, 'venomous': 0, 'venous': 0, 'vent': 0, 'ventilation': 0, 'ventilator': 0, 'ventricle': 0, 'ventricular': 0, 'venture': 0, 'venue': 0, 'veracity': 1, 'veranda': 0, 'verbal': 0, 'verbatim': 0, 'verbiage': 0, 'verbose': 0, 'verbosity': 0, 'verdant': 0, 'verdict': 0, 'verge': 0, 'verification': 0, 'verified': 0, 'verify': 0, 'verily': 0, 'veritable': 0, 'vermin': 0, 'vernacular': 0, 'vernal': 0, 'veronica': 0, 'versatile': 0, 'versatility': 0, 'verse': 0, 'version': 0, 'versus': 0, 'vert': 0, 'vertebra': 0, 'vertebral': 0, 'vertex': 0, 'vertical': 0, 'vertically': 0, 'vertigo': 0, 'verve': 0, 'vesicle': 0, 'vesicular': 0, 'vessel': 0, 'vest': 0, 'vested': 0, 'vestibule': 0, 'vestige': 0, 'vet': 0, 'veteran': 0, 'veterinarian': 0, 'veto': 0, 'viability': 0, 'viable': 0, 'viaduct': 0, 'vial': 0, 'vibrate': 0, 'vibration': 0, 'vibratory': 0, 'vicar': 0, 'vicarious': 0, 'vice': 0, 'vicinity': 0, 'vicious': 0, 'victim': 0, 'victimized': 1, 'victor': 0, 'victoria': 0, 'victorious': 0, 'victory': 0, 'videotape': 0, 'vie': 0, 'view': 0, 'vigil': 0, 'vigilance': 0, 'vigilant': 0, 'vignette': 0, 'vigor': 0, 'vigorous': 0, 'viking': 0, 'villa': 0, 'village': 0, 'villager': 0, 'villain': 0, 'villainous': 0, 'vinaigrette': 0, 'vindicate': 0, 'vindicated': 0, 'vindication': 0, 'vindictive': 0, 'vinegar': 0, 'vineyard': 0, 'viola': 0, 'violation': 1, 'violence': 0, 'violent': 1, 'violently': 0, 'violet': 0, 'violin': 0, 'violinist': 0, 'viper': 0, 'virgin': 0, 'virginity': 0, 'virology': 0, 'virtual': 0, 'virtually': 0, 'virtue': 0, 'virtuoso': 0, 'virtuous': 0, 'virulence': 0, 'virus': 0, 'visa': 0, 'visage': 0, 'viscosity': 0, 'viscous': 0, 'vise': 0, 'visibility': 0, 'visible': 0, 'visibly': 0, 'vision': 0, 'visionary': 0, 'visit': 0, 'visitation': 0, 'visiting': 0, 'visitor': 0, 'visor': 1, 'vista': 0, 'visual': 0, 'visualize': 0, 'vital': 0, 'vitality': 0, 'vitreous': 0, 'vivacious': 0, 'vivid': 0, 'vixen': 0, 'vocabulary': 0, 'vocal': 0, 'vocalist': 0, 'vocation': 0, 'vogue': 0, 'voice': 0, 'voiceless': 0, 'void': 0, 'volatility': 1, 'volcanic': 0, 'volcano': 1, 'volition': 0, 'volley': 0, 'voltmeter': 0, 'volume': 0, 'voluminous': 0, 'voluntarily': 0, 'voluntary': 0, 'volunteer': 0, 'volunteering': 0, 'volunteers': 0, 'voluptuous': 0, 'vomit': 0, 'vomiting': 0, 'voodoo': 0, 'voracious': 0, 'vortex': 0, 'vote': 1, 'voting': 0, 'votive': 0, 'vouch': 0, 'voucher': 0, 'vow': 0, 'vowel': 0, 'voyage': 0, 'voyager': 0, 'vulgar': 0, 'vulgarity': 0, 'vulnerability': 0, 'vulnerable': 0, 'vulture': 0, 'wad': 0, 'wade': 0, 'wafer': 0, 'waffle': 0, 'wag': 0, 'wager': 0, 'wages': 0, 'wagon': 0, 'wail': 0, 'waist': 0, 'waistcoat': 0, 'wait': 0, 'waiter': 0, 'waiting': 0, 'waive': 0, 'wake': 0, 'walk': 0, 'walker': 0, 'wall': 0, 'wallet': 0, 'wallow': 0, 'walnut': 0, 'waltz': 0, 'wan': 0, 'wand': 0, 'wander': 0, 'wanderer': 0, 'wandering': 0, 'wane': 0, 'waning': 0, 'wanting': 0, 'war': 0, 'warbler': 0, 'ward': 0, 'warden': 0, 'wardrobe': 0, 'ware': 0, 'warehouse': 0, 'warfare': 0, 'warlike': 0, 'warlock': 0, 'warming': 0, 'warn': 1, 'warned': 1, 'warning': 0, 'warp': 0, 'warped': 0, 'warrant': 0, 'warranted': 0, 'warrants': 0, 'warranty': 0, 'warren': 0, 'warrior': 0, 'wart': 0, 'wary': 0, 'wash': 0, 'washing': 0, 'washout': 0, 'wasp': 0, 'waste': 0, 'wasted': 0, 'wasteful': 0, 'wasting': 0, 'watch': 0, 'watchdog': 0, 'watchful': 0, 'watchman': 0, 'water': 0, 'watercourse': 0, 'watered': 0, 'waterproof': 0, 'waterworks': 0, 'watery': 0, 'wave': 0, 'waver': 0, 'wavering': 0, 'waves': 0, 'wavy': 0, 'wax': 0, 'waxy': 0, 'ways': 0, 'wayward': 0, 'weakened': 0, 'weakly': 0, 'weakness': 0, 'wealth': 0, 'wealthy': 0, 'weapon': 0, 'wear': 0, 'wearily': 0, 'weariness': 0, 'wearing': 0, 'weary': 0, 'weather': 0, 'weathered': 0, 'weatherproof': 0, 'weave': 0, 'web': 0, 'wed': 0, 'wedded': 0, 'wedge': 0, 'wee': 0, 'weed': 0, 'weeding': 0, 'weeds': 0, 'weedy': 0, 'week': 0, 'weekly': 0, 'weep': 0, 'weeping': 0, 'weigh': 0, 'weighing': 0, 'weight': 1, 'weightless': 0, 'weights': 0, 'weighty': 0, 'weir': 0, 'weird': 0, 'weirdo': 0, 'welcomed': 0, 'weld': 0, 'welfare': 0, 'wellhead': 0, 'welt': 0, 'wen': 0, 'wench': 0, 'western': 0, 'wet': 0, 'whack': 0, 'whale': 0, 'wham': 0, 'wharf': 0, 'whatsoever': 0, 'wheel': 0, 'wheels': 0, 'whereabouts': 0, 'wherefore': 0, 'wherewith': 0, 'wherewithal': 0, 'whet': 0, 'whiff': 0, 'whilst': 0, 'whim': 1, 'whimper': 0, 'whimsical': 0, 'whimsy': 0, 'whine': 0, 'whip': 0, 'whirl': 0, 'whirlpool': 0, 'whirlwind': 0, 'whisk': 0, 'whisker': 0, 'whisky': 0, 'whisper': 0, 'whispered': 0, 'whistle': 0, 'whit': 0, 'white': 0, 'whiteness': 0, 'whitish': 0, 'whiz': 0, 'wholesome': 0, 'wholly': 0, 'whoop': 0, 'whopping': 0, 'whore': 0, 'wick': 0, 'wicked': 0, 'wickedness': 0, 'wicker': 0, 'wicket': 0, 'wide': 0, 'widely': 0, 'widen': 0, 'widespread': 0, 'widow': 0, 'widower': 0, 'width': 0, 'wield': 0, 'wife': 0, 'wig': 0, 'wight': 0, 'wild': 1, 'wildcat': 0, 'wilderness': 0, 'wildfire': 1, 'willful': 0, 'willingly': 0, 'willingness': 0, 'willow': 0, 'wilted': 0, 'wily': 0, 'wimp': 0, 'wimpy': 0, 'wince': 0, 'winch': 0, 'wind': 0, 'windfall': 0, 'winding': 0, 'windmill': 0, 'window': 0, 'windy': 0, 'wine': 0, 'wing': 0, 'winged': 0, 'wink': 0, 'winner': 1, 'winning': 1, 'winnings': 0, 'winter': 0, 'wintry': 0, 'wipe': 0, 'wire': 0, 'wireless': 1, 'wis': 0, 'wisdom': 0, 'wise': 0, 'wishful': 0, 'wistful': 0, 'wit': 0, 'witch': 0, 'witchcraft': 0, 'withal': 0, 'withdraw': 0, 'withdrawal': 0, 'wither': 0, 'withered': 0, 'withstand': 0, 'witness': 0, 'wits': 0, 'witty': 0, 'wizard': 1, 'woe': 0, 'woeful': 0, 'woefully': 0, 'woman': 0, 'womanhood': 0, 'womanly': 0, 'womb': 0, 'wonderful': 1, 'wonderfully': 1, 'wondrous': 0, 'wont': 0, 'woo': 0, 'wood': 0, 'woodcut': 0, 'wooden': 0, 'woodlands': 0, 'woody': 0, 'wooing': 0, 'wool': 0, 'woolly': 0, 'wop': 0, 'word': 0, 'wording': 0, 'words': 0, 'wordy': 0, 'work': 0, 'workbook': 0, 'worker': 0, 'working': 0, 'workman': 0, 'workmanship': 0, 'workplace': 0, 'works': 0, 'workshop': 0, 'world': 0, 'worldly': 0, 'worldwide': 0, 'worm': 1, 'worn': 0, 'worried': 0, 'worry': 0, 'worrying': 0, 'worse': 0, 'worsening': 0, 'worship': 0, 'worth': 0, 'worthless': 0, 'worthy': 0, 'wot': 0, 'wound': 0, 'wrangler': 0, 'wrangling': 0, 'wrap': 0, 'wrapper': 0, 'wrapping': 0, 'wrath': 0, 'wreak': 0, 'wreath': 0, 'wreck': 1, 'wrecked': 0, 'wrench': 0, 'wrest': 0, 'wrestle': 0, 'wrestler': 0, 'wrestling': 0, 'wretch': 0, 'wretched': 0, 'wright': 0, 'wring': 0, 'wrinkle': 0, 'wrinkled': 0, 'wrist': 0, 'wristband': 0, 'wristwatch': 0, 'writ': 0, 'write': 0, 'writer': 0, 'writing': 0, 'written': 0, 'wrong': 0, 'wrongdoing': 0, 'wrongful': 0, 'wrongly': 0, 'wrought': 0, 'wry': 0, 'xenophobia': 0, 'xerox': 0, 'yacht': 0, 'yachting': 0, 'yak': 0, 'yam': 0, 'yank': 0, 'yard': 0, 'yarn': 0, 'yaw': 0, 'yawn': 0, 'yawning': 0, 'yea': 0, 'year': 0, 'yearbook': 0, 'yearling': 0, 'yearly': 0, 'yearn': 0, 'yearning': 0, 'years': 0, 'yeast': 0, 'yell': 1, 'yellow': 0, 'yellows': 0, 'yelp': 1, 'yeoman': 0, 'yesterday': 0, 'yesteryear': 0, 'yew': 0, 'yield': 0, 'yielding': 0, 'yogi': 0, 'yoke': 0, 'yolk': 0, 'yon': 0, 'yonder': 0, 'young': 1, 'younger': 0, 'youth': 1, 'zany': 1, 'zap': 0, 'zeal': 1, 'zealot': 0, 'zealous': 0, 'zebra': 0, 'zenith': 0, 'zephyr': 0, 'zeppelin': 0, 'zest': 0, 'zip': 0, 'zodiac': 0, 'zone': 0, 'zoo': 0, 'zoological': 0, 'zoology': 0, 'zoom': 0}
#For each record
#For each word in record
#Get the word score (score is a number if the word is in Lexicon, 0 if not)
#Add all the scores and find the ploarity
surprisenrc = []
strength =[]
for record in corpus:
#print("record", record)
score = 0
words = record.replace("'","").lower().split()
for word in words:
#print("word", word)
if word in (lexicons):
score = score + lexicons[word]
#print("score",score)
strength.append(score)
#print('strength',strength)
if (score > 0):
surprisenrc.append('1')
else:
surprisenrc.append('0')
#else:
# prediction.append('neutral')
print(surprisenrc)
#print(prediction)
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df_new['surprisenrc']= surprisenrc
df_new.head()
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | tokenized_docs_no_stopwords | preprocessed_docs | word_final | ... | prediction_affin | positivenrc | negativenrc | angernrc | anticipationnrc | disgustnrc | fearnrc | joynrc | sadnessnrc | surprisenrc | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | case id worst poor customer service giving res... | ... | negative | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 1 | 0 |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | ['please', 'dont', 'install', 'this', 'app', '... | ['please', 'dont', 'install', 'app', 'people',... | ['please', 'dont', 'install', 'app', 'people',... | please dont install app people stole informati... | ... | negative | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... | ['dont', 'waste', 'your', 'time', 'and', 'mone... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | dont waste time money woohoo payment successfu... | ... | positive | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 1 |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | worst customer supportthey wont pick call wont... | ... | negative | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... | ['was', 'a', 'happy', 'customer', 'till', 'i',... | ['happy', 'customer', 'till', 'faced', 'error'... | ['happy', 'customer', 'till', 'faced', 'error'... | happy customer till faced error guess even don... | ... | neutral | 1 | 1 | 0 | 1 | 0 | 0 | 1 | 1 | 1 |
5 rows × 21 columns
#Read the lexicon file
lex_file = open("D:\\11 Project\\Project\\NRC_file - trust.csv")
lexicons = {}
records = lex_file.readlines()
for record in records:
#print(record) # line contains newline charecter
#print(record.rstrip('\n').split(",")) - to remove new line charecter
lexicons[record.rstrip('\n').split(",")[0]] = int(record.rstrip('\n').split(",")[1])
print(lexicons)
{'aback': 0, 'abacus': 1, 'abandon': 0, 'abandoned': 0, 'abandonment': 0, 'abate': 0, 'abatement': 0, 'abba': 0, 'abbot': 1, 'abbreviate': 0, 'abbreviation': 0, 'abdomen': 0, 'abdominal': 0, 'abduction': 0, 'aberrant': 0, 'aberration': 0, 'abeyance': 0, 'abhor': 0, 'abhorrent': 0, 'abide': 0, 'ability': 0, 'abject': 0, 'ablation': 0, 'ablaze': 0, 'abnormal': 0, 'aboard': 0, 'abode': 0, 'abolish': 0, 'abolition': 0, 'abominable': 0, 'abomination': 0, 'aboriginal': 0, 'abort': 0, 'abortion': 0, 'abortive': 0, 'abound': 0, 'abovementioned': 0, 'abrasion': 0, 'abroad': 0, 'abrogate': 0, 'abrupt': 0, 'abruptly': 0, 'abscess': 0, 'absence': 0, 'absent': 0, 'absentee': 0, 'absenteeism': 0, 'absinthe': 0, 'absolute': 0, 'absolution': 1, 'absorbed': 0, 'absorbent': 0, 'absorbing': 0, 'absorption': 0, 'abstain': 0, 'abstention': 0, 'abstinence': 0, 'abstract': 0, 'abstraction': 0, 'absurd': 0, 'absurdity': 0, 'abundance': 1, 'abundant': 0, 'abuse': 0, 'abutment': 0, 'aby': 0, 'abysmal': 0, 'abyss': 0, 'academic': 1, 'academy': 0, 'accede': 0, 'accelerate': 0, 'acceleration': 0, 'accent': 0, 'accentuate': 0, 'accept': 0, 'acceptable': 0, 'acceptance': 0, 'access': 0, 'accessible': 0, 'accession': 0, 'accessory': 0, 'accident': 0, 'accidental': 0, 'accidentally': 0, 'accolade': 1, 'accommodate': 0, 'accommodation': 0, 'accompaniment': 1, 'accompany': 0, 'accompanying': 0, 'accomplice': 0, 'accomplish': 0, 'accomplished': 0, 'accomplishment': 0, 'accord': 1, 'accordance': 0, 'accordion': 0, 'account': 1, 'accountability': 1, 'accountable': 1, 'accountant': 1, 'accounting': 0, 'accounts': 1, 'accredited': 1, 'accretion': 0, 'accrue': 0, 'accueil': 0, 'accumulate': 0, 'accumulation': 0, 'accuracy': 0, 'accurate': 1, 'accursed': 0, 'accusation': 0, 'accusative': 0, 'accused': 0, 'accuser': 0, 'accusing': 0, 'accustomed': 0, 'ace': 0, 'acetic': 0, 'ache': 0, 'achieve': 1, 'achievement': 1, 'aching': 0, 'acid': 0, 'acidity': 0, 'acknowledge': 0, 'acknowledged': 0, 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'wheels': 0, 'whereabouts': 0, 'wherefore': 0, 'wherewith': 0, 'wherewithal': 0, 'whet': 0, 'whiff': 0, 'whilst': 0, 'whim': 0, 'whimper': 0, 'whimsical': 0, 'whimsy': 0, 'whine': 0, 'whip': 0, 'whirl': 0, 'whirlpool': 0, 'whirlwind': 0, 'whisk': 0, 'whisker': 0, 'whisky': 0, 'whisper': 0, 'whispered': 0, 'whistle': 0, 'whit': 0, 'white': 1, 'whiteness': 0, 'whitish': 0, 'whiz': 0, 'wholesome': 1, 'wholly': 0, 'whoop': 0, 'whopping': 0, 'whore': 0, 'wick': 0, 'wicked': 0, 'wickedness': 0, 'wicker': 0, 'wicket': 0, 'wide': 0, 'widely': 0, 'widen': 0, 'widespread': 0, 'widow': 0, 'widower': 0, 'width': 0, 'wield': 0, 'wife': 0, 'wig': 0, 'wight': 0, 'wild': 0, 'wildcat': 0, 'wilderness': 0, 'wildfire': 0, 'willful': 0, 'willingly': 0, 'willingness': 0, 'willow': 0, 'wilted': 0, 'wily': 0, 'wimp': 0, 'wimpy': 0, 'wince': 0, 'winch': 0, 'wind': 0, 'windfall': 0, 'winding': 0, 'windmill': 0, 'window': 0, 'windy': 0, 'wine': 0, 'wing': 0, 'winged': 0, 'wink': 0, 'winner': 0, 'winning': 1, 'winnings': 0, 'winter': 0, 'wintry': 0, 'wipe': 0, 'wire': 0, 'wireless': 0, 'wis': 0, 'wisdom': 1, 'wise': 0, 'wishful': 0, 'wistful': 0, 'wit': 0, 'witch': 0, 'witchcraft': 0, 'withal': 0, 'withdraw': 0, 'withdrawal': 0, 'wither': 0, 'withered': 0, 'withstand': 0, 'witness': 1, 'wits': 0, 'witty': 0, 'wizard': 0, 'woe': 0, 'woeful': 0, 'woefully': 0, 'woman': 0, 'womanhood': 0, 'womanly': 0, 'womb': 0, 'wonderful': 1, 'wonderfully': 0, 'wondrous': 0, 'wont': 0, 'woo': 0, 'wood': 0, 'woodcut': 0, 'wooden': 0, 'woodlands': 0, 'woody': 0, 'wooing': 0, 'wool': 0, 'woolly': 0, 'wop': 0, 'word': 1, 'wording': 0, 'words': 0, 'wordy': 0, 'work': 0, 'workbook': 0, 'worker': 0, 'working': 0, 'workman': 0, 'workmanship': 0, 'workplace': 0, 'works': 0, 'workshop': 0, 'world': 0, 'worldly': 0, 'worldwide': 0, 'worm': 0, 'worn': 0, 'worried': 0, 'worry': 0, 'worrying': 0, 'worse': 0, 'worsening': 0, 'worship': 1, 'worth': 0, 'worthless': 0, 'worthy': 1, 'wot': 1, 'wound': 0, 'wrangler': 0, 'wrangling': 0, 'wrap': 0, 'wrapper': 0, 'wrapping': 0, 'wrath': 0, 'wreak': 0, 'wreath': 0, 'wreck': 0, 'wrecked': 0, 'wrench': 0, 'wrest': 0, 'wrestle': 0, 'wrestler': 0, 'wrestling': 0, 'wretch': 0, 'wretched': 0, 'wright': 0, 'wring': 0, 'wrinkle': 0, 'wrinkled': 0, 'wrist': 0, 'wristband': 0, 'wristwatch': 0, 'writ': 0, 'write': 0, 'writer': 0, 'writing': 0, 'written': 0, 'wrong': 0, 'wrongdoing': 0, 'wrongful': 0, 'wrongly': 0, 'wrought': 0, 'wry': 0, 'xenophobia': 0, 'xerox': 0, 'yacht': 0, 'yachting': 0, 'yak': 0, 'yam': 0, 'yank': 0, 'yard': 0, 'yarn': 0, 'yaw': 0, 'yawn': 0, 'yawning': 0, 'yea': 0, 'year': 0, 'yearbook': 0, 'yearling': 0, 'yearly': 0, 'yearn': 0, 'yearning': 1, 'years': 0, 'yeast': 0, 'yell': 0, 'yellow': 0, 'yellows': 0, 'yelp': 0, 'yeoman': 0, 'yesterday': 0, 'yesteryear': 0, 'yew': 0, 'yield': 0, 'yielding': 0, 'yogi': 0, 'yoke': 0, 'yolk': 0, 'yon': 0, 'yonder': 0, 'young': 0, 'younger': 0, 'youth': 0, 'zany': 0, 'zap': 0, 'zeal': 1, 'zealot': 0, 'zealous': 1, 'zebra': 0, 'zenith': 0, 'zephyr': 0, 'zeppelin': 0, 'zest': 1, 'zip': 0, 'zodiac': 0, 'zone': 0, 'zoo': 0, 'zoological': 0, 'zoology': 0, 'zoom': 0}
#For each record
#For each word in record
#Get the word score (score is a number if the word is in Lexicon, 0 if not)
#Add all the scores and find the ploarity
trustnrc = []
strength =[]
for record in corpus:
#print("record", record)
score = 0
words = record.replace("'","").lower().split()
for word in words:
#print("word", word)
if word in (lexicons):
score = score + lexicons[word]
#print("score",score)
strength.append(score)
#print('strength',strength)
if (score > 0):
trustnrc.append('1')
else:
trustnrc.append('0')
#else:
# prediction.append('neutral')
print(trustnrc)
#print(prediction)
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df_new['trustnrc']= trustnrc
df_new.head()
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | tokenized_docs_no_stopwords | preprocessed_docs | word_final | ... | positivenrc | negativenrc | angernrc | anticipationnrc | disgustnrc | fearnrc | joynrc | sadnessnrc | surprisenrc | trustnrc | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | case id worst poor customer service giving res... | ... | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | ['please', 'dont', 'install', 'this', 'app', '... | ['please', 'dont', 'install', 'app', 'people',... | ['please', 'dont', 'install', 'app', 'people',... | please dont install app people stole informati... | ... | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 1 |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... | ['dont', 'waste', 'your', 'time', 'and', 'mone... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | dont waste time money woohoo payment successfu... | ... | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 1 |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | worst customer supportthey wont pick call wont... | ... | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... | ['was', 'a', 'happy', 'customer', 'till', 'i',... | ['happy', 'customer', 'till', 'faced', 'error'... | ['happy', 'customer', 'till', 'faced', 'error'... | happy customer till faced error guess even don... | ... | 1 | 1 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 1 |
5 rows × 22 columns
#pd.crosstab(test_affin['Rating'], test_affin['prediction'])
#pd.crosstab(test_affin.Rating, test_affin.prediction).apply(lambda r: r/len(df), axis=1)
#from sklearn.model_selection import train_test_split
#train, test = train_test_split(df_word, test_size=0.3, random_state=1)
VADER stands for Valence Aware Dictionary and sEntiment Reasoner. It is a rule-based sentiment analyzer.It consists of a list of lexical features (e.g. words) which are generally labeled as per their semantic orientation as positive or negative.
Please install VaderSentiment, if doing for the firstt time
#! pip install vaderSentiment
Collecting vaderSentiment Downloading vaderSentiment-3.3.2-py2.py3-none-any.whl (125 kB) Requirement already satisfied: requests in d:\installed_softwares_c_drive\anaconda3\lib\site-packages (from vaderSentiment) (2.25.1) Requirement already satisfied: idna<3,>=2.5 in d:\installed_softwares_c_drive\anaconda3\lib\site-packages (from requests->vaderSentiment) (2.10) Requirement already satisfied: urllib3<1.27,>=1.21.1 in d:\installed_softwares_c_drive\anaconda3\lib\site-packages (from requests->vaderSentiment) (1.26.4) Requirement already satisfied: chardet<5,>=3.0.2 in d:\installed_softwares_c_drive\anaconda3\lib\site-packages (from requests->vaderSentiment) (4.0.0) Requirement already satisfied: certifi>=2017.4.17 in d:\installed_softwares_c_drive\anaconda3\lib\site-packages (from requests->vaderSentiment) (2020.12.5) Installing collected packages: vaderSentiment Successfully installed vaderSentiment-3.3.2
nltk.download('vader_lexicon')
[nltk_data] Downloading package vader_lexicon to C:\Users\Harsha [nltk_data] GV\AppData\Roaming\nltk_data...
True
#from sklearn.model_selection import train_test_split
#train, test = train_test_split(df_word, test_size=0.3, random_state=1)
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
analyzer = SentimentIntensityAnalyzer()
#create a object/instance
#Generating Sentiment for all the sentence present in the dataset
emptyline=[]
for row in df_new['word_final']:
vs=analyzer.polarity_scores(row)
emptyline.append(vs)
# Creating new dataframe with sentiments
df_sentiments =pd.DataFrame(emptyline)
df_sentiments
| neg | neu | pos | compound | |
|---|---|---|---|---|
| 0 | 0.312 | 0.519 | 0.169 | -0.7380 |
| 1 | 0.175 | 0.706 | 0.120 | -0.2023 |
| 2 | 0.000 | 0.507 | 0.493 | 0.9386 |
| 3 | 0.208 | 0.732 | 0.059 | -0.7430 |
| 4 | 0.233 | 0.548 | 0.219 | -0.1027 |
| ... | ... | ... | ... | ... |
| 2777 | 0.000 | 0.000 | 1.000 | 0.4215 |
| 2778 | 0.000 | 0.000 | 1.000 | 0.5994 |
| 2779 | 0.000 | 0.000 | 1.000 | 0.6808 |
| 2780 | 0.000 | 0.000 | 1.000 | 0.7003 |
| 2781 | 0.000 | 0.000 | 1.000 | 0.6249 |
2782 rows × 4 columns
#Merging the sentiments back to reviews dataframe
df_new = pd.concat([df_new.reset_index(drop=True), df_sentiments], axis=1)
df_new.head(5)
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | tokenized_docs_no_stopwords | preprocessed_docs | word_final | ... | disgustnrc | fearnrc | joynrc | sadnessnrc | surprisenrc | trustnrc | neg | neu | pos | compound | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | case id worst poor customer service giving res... | ... | 0 | 1 | 0 | 1 | 0 | 0 | 0.312 | 0.519 | 0.169 | -0.7380 |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | ['please', 'dont', 'install', 'this', 'app', '... | ['please', 'dont', 'install', 'app', 'people',... | ['please', 'dont', 'install', 'app', 'people',... | please dont install app people stole informati... | ... | 1 | 0 | 1 | 0 | 0 | 1 | 0.175 | 0.706 | 0.120 | -0.2023 |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... | ['dont', 'waste', 'your', 'time', 'and', 'mone... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | dont waste time money woohoo payment successfu... | ... | 1 | 0 | 1 | 0 | 1 | 1 | 0.000 | 0.507 | 0.493 | 0.9386 |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | worst customer supportthey wont pick call wont... | ... | 0 | 0 | 0 | 0 | 0 | 1 | 0.208 | 0.732 | 0.059 | -0.7430 |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... | ['was', 'a', 'happy', 'customer', 'till', 'i',... | ['happy', 'customer', 'till', 'faced', 'error'... | ['happy', 'customer', 'till', 'faced', 'error'... | happy customer till faced error guess even don... | ... | 0 | 0 | 1 | 1 | 1 | 1 | 0.233 | 0.548 | 0.219 | -0.1027 |
5 rows × 26 columns
#Convert Scores into positive and negative sentiments using some threshold
df_new['VSentiment'] =np.where(df_new['compound'] >=0 , 'Positive' ,'Negative')
df_new.head(5)
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | tokenized_docs_no_stopwords | preprocessed_docs | word_final | ... | fearnrc | joynrc | sadnessnrc | surprisenrc | trustnrc | neg | neu | pos | compound | VSentiment | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | case id worst poor customer service giving res... | ... | 1 | 0 | 1 | 0 | 0 | 0.312 | 0.519 | 0.169 | -0.7380 | Negative |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | ['please', 'dont', 'install', 'this', 'app', '... | ['please', 'dont', 'install', 'app', 'people',... | ['please', 'dont', 'install', 'app', 'people',... | please dont install app people stole informati... | ... | 0 | 1 | 0 | 0 | 1 | 0.175 | 0.706 | 0.120 | -0.2023 | Negative |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... | ['dont', 'waste', 'your', 'time', 'and', 'mone... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | dont waste time money woohoo payment successfu... | ... | 0 | 1 | 0 | 1 | 1 | 0.000 | 0.507 | 0.493 | 0.9386 | Positive |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | worst customer supportthey wont pick call wont... | ... | 0 | 0 | 0 | 0 | 1 | 0.208 | 0.732 | 0.059 | -0.7430 | Negative |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... | ['was', 'a', 'happy', 'customer', 'till', 'i',... | ['happy', 'customer', 'till', 'faced', 'error'... | ['happy', 'customer', 'till', 'faced', 'error'... | happy customer till faced error guess even don... | ... | 0 | 1 | 1 | 1 | 1 | 0.233 | 0.548 | 0.219 | -0.1027 | Negative |
5 rows × 27 columns
df_new.to_excel(r'D:\\11 Project\\Project\\Data_output_sentiment.xlsx', index = False)
pd.crosstab(train_v_table['Rating'], train_v_table['VSentiment'])
pd.crosstab(train_v_table.Rating, train_v_table.VSentiment).apply(lambda r: r/len(df), axis=1)
result=train_v_table['VSentiment'].value_counts() result.plot(kind='bar' , rot=0, color=['plum', 'cyan'])
df_word = df_new
from wordcloud import WordCloud
import matplotlib.pyplot as plt
# Polarity == 1 ONE STAR RATING
df_word1_s1 = df_word[df_word.Rating ==1]
all_text = ' '.join(word for word in df_word1_s1.word_final)
wordcloud = WordCloud(colormap='Reds', width=1000, height=1000, mode='RGBA', background_color='white').generate(all_text)
plt.figure(figsize=(20,10))
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis("off")
plt.margins(x=0, y=0)
plt.show()
# Polarity == 2 TWO STAR RATING
df_word1_s2 = df_word[df_word.Rating ==2]
all_text = ' '.join(word for word in df_word1_s2.word_final)
wordcloud = WordCloud(width=1000, height=1000, colormap='Blues', background_color='white', mode='RGBA').generate(all_text)
plt.figure( figsize=(20,10))
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis("off")
plt.margins(x=0, y=0)
plt.show()
# Polarity == 3 THREE STAR RATING
df_word1_s3 = df_word[df_word.Rating ==3]
all_text = ' '.join(word for word in df_word1_s3.word_final)
wordcloud_p2 = WordCloud(width=1000, height=1000, colormap='Wistia',background_color='white', mode='RGBA').generate(all_text)
plt.figure(figsize=(20,10))
plt.imshow(wordcloud_p2, interpolation='bilinear')
plt.axis("off")
plt.margins(x=0, y=0)
plt.show()
# Polarity == 4 THREE STAR RATING
df_word1_s4 = df_word[df_word.Rating ==4]
all_text = ' '.join(word for word in df_word1_s4.word_final)
wordcloud_p2 = WordCloud(width=1000, height=1000, colormap='PuBuGn',background_color='white', mode='RGBA').generate(all_text)
plt.figure(figsize=(20,10))
plt.imshow(wordcloud_p2, interpolation='bilinear')
plt.axis("off")
plt.margins(x=0, y=0)
plt.show()
# Polarity == 5 THREE STAR RATING
df_word1_s5 = df_word[df_word.Rating ==5]
all_text = ' '.join(word for word in df_word1_s5.word_final)
wordcloud_p2 = WordCloud(width=1000, height=1000, colormap='GnBu',background_color='white', mode='RGBA').generate(all_text)
plt.figure(figsize=(20,10))
plt.imshow(wordcloud_p2, interpolation='bilinear')
plt.axis("off")
plt.margins(x=0, y=0)
plt.show()
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from wordcloud import WordCloud
import matplotlib.pyplot as plt
# Polarity == positivenrc
df_word1_s6 = df_word[df_word.positivenrc =='1']
all_text = ' '.join(word for word in df_word1_s6.word_final)
wordcloud = WordCloud(colormap='Reds', width=1000, height=1000, mode='RGBA', background_color='white').generate(all_text)
plt.figure(figsize=(20,10))
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis("off")
plt.margins(x=0, y=0)
plt.show()
# Polarity == negativenrc
df_word1_s7 = df_word[df_word.negativenrc =='1']
all_text = ' '.join(word for word in df_word1_s7.word_final)
wordcloud = WordCloud(width=1000, height=1000, colormap='Blues', background_color='white', mode='RGBA').generate(all_text)
plt.figure( figsize=(20,10))
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis("off")
plt.margins(x=0, y=0)
plt.show()
# Polarity == angernrc
df_word1_s8 = df_word[df_word.angernrc =='1']
all_text = ' '.join(word for word in df_word1_s8.word_final)
wordcloud_p2 = WordCloud(width=1000, height=1000, colormap='Wistia',background_color='white', mode='RGBA').generate(all_text)
plt.figure(figsize=(20,10))
plt.imshow(wordcloud_p2, interpolation='bilinear')
plt.axis("off")
plt.margins(x=0, y=0)
plt.show()
# Polarity == anticipationnrc
df_word1_s9 = df_word[df_word.anticipationnrc =='1']
all_text = ' '.join(word for word in df_word1_s9.word_final)
wordcloud_p2 = WordCloud(width=1000, height=1000, colormap='gist_heat',background_color='white', mode='RGBA').generate(all_text)
plt.figure(figsize=(20,10))
plt.imshow(wordcloud_p2, interpolation='bilinear')
plt.axis("off")
plt.margins(x=0, y=0)
plt.show()
# Polarity == disgustnrc
df_word1_s10 = df_word[df_word.disgustnrc =='1']
all_text = ' '.join(word for word in df_word1_s10.word_final)
wordcloud_p2 = WordCloud(width=1000, height=1000, colormap='GnBu',background_color='white', mode='RGBA').generate(all_text)
plt.figure(figsize=(20,10))
plt.imshow(wordcloud_p2, interpolation='bilinear')
plt.axis("off")
plt.margins(x=0, y=0)
plt.show()
# Polarity == fearnrc
df_word1_s11 = df_word[df_word.fearnrc =='1']
all_text = ' '.join(word for word in df_word1_s11.word_final)
wordcloud_p2 = WordCloud(width=1000, height=1000, colormap='RdPu',background_color='white', mode='RGBA').generate(all_text)
plt.figure(figsize=(20,10))
plt.imshow(wordcloud_p2, interpolation='bilinear')
plt.axis("off")
plt.margins(x=0, y=0)
plt.show()
# Polarity == joynrc
df_word1_s12 = df_word[df_word.joynrc =='1']
all_text = ' '.join(word for word in df_word1_s12.word_final)
wordcloud_p2 = WordCloud(width=1000, height=1000, colormap='YlGn',background_color='white', mode='RGBA').generate(all_text)
plt.figure(figsize=(20,10))
plt.imshow(wordcloud_p2, interpolation='bilinear')
plt.axis("off")
plt.margins(x=0, y=0)
plt.show()
# Polarity == sadnessnrc
df_word1_s13 = df_word[df_word.sadnessnrc =='1']
all_text = ' '.join(word for word in df_word1_s13.word_final)
wordcloud_p2 = WordCloud(width=1000, height=1000, colormap='coolwarm',background_color='white', mode='RGBA').generate(all_text)
plt.figure(figsize=(20,10))
plt.imshow(wordcloud_p2, interpolation='bilinear')
plt.axis("off")
plt.margins(x=0, y=0)
plt.show()
# Polarity == surprisenrc
df_word1_s14 = df_word[df_word.surprisenrc =='1']
all_text = ' '.join(word for word in df_word1_s14.word_final)
wordcloud_p2 = WordCloud(width=1000, height=1000, colormap='BrBG',background_color='white', mode='RGBA').generate(all_text)
plt.figure(figsize=(20,10))
plt.imshow(wordcloud_p2, interpolation='bilinear')
plt.axis("off")
plt.margins(x=0, y=0)
plt.show()
# Polarity == trustnrc
df_word1_s15 = df_word[df_word.trustnrc =='1']
all_text = ' '.join(word for word in df_word1_s15.word_final)
wordcloud_p2 = WordCloud(width=1000, height=1000, colormap='seismic',background_color='white', mode='RGBA').generate(all_text)
plt.figure(figsize=(20,10))
plt.imshow(wordcloud_p2, interpolation='bilinear')
plt.axis("off")
plt.margins(x=0, y=0)
plt.show()
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#Read the unlabelled Google reviews set
df = pd.read_excel("D:\\11 Project\\Project\\Data_output_sentiment.xlsx'")
#Import the libraries
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from collections import Counter
from sklearn import feature_extraction, model_selection, naive_bayes, metrics, svm
%matplotlib inline
# Print multiple statements in same line
from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity = "all"
#Read the data
data = pd.read_excel("D:\\11 Project\\Project\\Data_output_sentiment.xlsx")
data.head(n=10)
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | tokenized_docs_no_stopwords | preprocessed_docs | word_final | ... | fearnrc | joynrc | sadnessnrc | surprisenrc | trustnrc | neg | neu | pos | compound | VSentiment | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | case id worst poor customer service giving res... | ... | 1 | 0 | 1 | 0 | 0 | 0.312 | 0.519 | 0.169 | -0.7380 | Negative |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | ['please', 'dont', 'install', 'this', 'app', '... | ['please', 'dont', 'install', 'app', 'people',... | ['please', 'dont', 'install', 'app', 'people',... | please dont install app people stole informati... | ... | 0 | 1 | 0 | 0 | 1 | 0.175 | 0.706 | 0.120 | -0.2023 | Negative |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... | ['dont', 'waste', 'your', 'time', 'and', 'mone... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | dont waste time money woohoo payment successfu... | ... | 0 | 1 | 0 | 1 | 1 | 0.000 | 0.507 | 0.493 | 0.9386 | Positive |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | worst customer supportthey wont pick call wont... | ... | 0 | 0 | 0 | 0 | 1 | 0.208 | 0.732 | 0.059 | -0.7430 | Negative |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... | ['was', 'a', 'happy', 'customer', 'till', 'i',... | ['happy', 'customer', 'till', 'faced', 'error'... | ['happy', 'customer', 'till', 'faced', 'error'... | happy customer till faced error guess even don... | ... | 0 | 1 | 1 | 1 | 1 | 0.233 | 0.548 | 0.219 | -0.1027 | Negative |
| 5 | 1 | 2021 | Negative | My money was deducted 10000 then called verifi... | my money was deducted then called verificatio... | my money was deducted then called verificatio... | ['my', 'money', 'was', 'deducted', 'then', 'ca... | ['money', 'deducted', 'called', 'verification'... | ['money', 'deducted', 'called', 'verification'... | money deducted called verification call called... | ... | 0 | 1 | 0 | 1 | 1 | 0.000 | 0.722 | 0.278 | 0.6597 | Positive |
| 6 | 1 | 2021 | Negative | They charge you and won't issue the gift cards... | they charge you and wont issue the gift cards ... | they charge you and wont issue the gift cards ... | ['they', 'charge', 'you', 'and', 'wont', 'issu... | ['charge', 'wont', 'issue', 'gift', 'cards', '... | ['charge', 'wont', 'issue', 'gift', 'card', 'c... | charge wont issue gift card careful pathetic c... | ... | 0 | 1 | 1 | 1 | 0 | 0.389 | 0.509 | 0.102 | -0.6711 | Negative |
| 7 | 1 | 2021 | Negative | Poor customer service. Lost 4.5k Money debited... | poor customer service lost money debited but ... | poor customer service lost money debited but ... | ['poor', 'customer', 'service', 'lost', 'money... | ['poor', 'customer', 'service', 'lost', 'money... | ['poor', 'customer', 'service', 'lost', 'money... | poor customer service lost money debited gc ge... | ... | 0 | 1 | 1 | 1 | 1 | 0.316 | 0.585 | 0.099 | -0.5719 | Negative |
| 8 | 1 | 2021 | Negative | I am stuck with it since the entire day. And M... | i am stuck with it since the entire day and my... | i am stuck with it since the entire day and my... | ['i', 'am', 'stuck', 'with', 'it', 'since', 't... | ['stuck', 'since', 'entire', 'day', 'coupons',... | ['stuck', 'since', 'entire', 'day', 'coupon', ... | stuck since entire day coupon yet processed re... | ... | 0 | 0 | 0 | 0 | 1 | 0.335 | 0.520 | 0.145 | -0.5106 | Negative |
| 9 | 1 | 2021 | Negative | The service of this company is pathetic the mo... | the service of this company is pathetic the mo... | the service of this company is pathetic the mo... | ['the', 'service', 'of', 'this', 'company', 'i... | ['service', 'company', 'pathetic', 'money', 'd... | ['service', 'company', 'pathetic', 'money', 'd... | service company pathetic money debited account... | ... | 0 | 1 | 1 | 1 | 1 | 0.340 | 0.560 | 0.100 | -0.7184 | Negative |
10 rows × 27 columns
data.columns
Index(['Rating', 'Year', 'Sentiment', 'Review', 'cleaned_description',
'cleaned_description_new', 'words', 'tokenized_docs_no_stopwords',
'preprocessed_docs', 'word_final', 'strength_affin', 'prediction_affin',
'positivenrc', 'negativenrc', 'angernrc', 'anticipationnrc',
'disgustnrc', 'fearnrc', 'joynrc', 'sadnessnrc', 'surprisenrc',
'trustnrc', 'neg', 'neu', 'pos', 'compound', 'VSentiment'],
dtype='object')
data['length'] = data['word_final'].apply(len)
data.head()
| Rating | Year | Sentiment | Review | cleaned_description | cleaned_description_new | words | tokenized_docs_no_stopwords | preprocessed_docs | word_final | ... | joynrc | sadnessnrc | surprisenrc | trustnrc | neg | neu | pos | compound | VSentiment | length | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2021 | Negative | ##10103920## case I'd Worst poor customer serv... | case id worst poor customer service they are ... | case id worst poor customer service they are ... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | ['case', 'id', 'worst', 'poor', 'customer', 's... | case id worst poor customer service giving res... | ... | 0 | 1 | 0 | 0 | 0.312 | 0.519 | 0.169 | -0.7380 | Negative | 179 |
| 1 | 1 | 2021 | Negative | Please don't install this app. people stole al... | please dont install this app people stole all ... | please dont install this app people stole all ... | ['please', 'dont', 'install', 'this', 'app', '... | ['please', 'dont', 'install', 'app', 'people',... | ['please', 'dont', 'install', 'app', 'people',... | please dont install app people stole informati... | ... | 1 | 0 | 0 | 1 | 0.175 | 0.706 | 0.120 | -0.2023 | Negative | 191 |
| 2 | 1 | 2021 | Negative | Don't waste your time and money on Woohoo. Pay... | dont waste your time and money on woohoo payme... | dont waste your time and money on woohoo payme... | ['dont', 'waste', 'your', 'time', 'and', 'mone... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | ['dont', 'waste', 'time', 'money', 'woohoo', '... | dont waste time money woohoo payment successfu... | ... | 1 | 0 | 1 | 1 | 0.000 | 0.507 | 0.493 | 0.9386 | Positive | 129 |
| 3 | 1 | 2021 | Negative | Worst customer support...They won't pick calls... | worst customer supportthey wont pick calls and... | worst customer supportthey wont pick calls and... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | ['worst', 'customer', 'supportthey', 'wont', '... | worst customer supportthey wont pick call wont... | ... | 0 | 0 | 0 | 1 | 0.208 | 0.732 | 0.059 | -0.7430 | Negative | 200 |
| 4 | 1 | 2021 | Negative | Was a happy customer till I faced an error and... | was a happy customer till i faced an error and... | was a happy customer till i faced an error and... | ['was', 'a', 'happy', 'customer', 'till', 'i',... | ['happy', 'customer', 'till', 'faced', 'error'... | ['happy', 'customer', 'till', 'faced', 'error'... | happy customer till faced error guess even don... | ... | 1 | 1 | 1 | 1 | 0.233 | 0.548 | 0.219 | -0.1027 | Negative | 118 |
5 rows × 28 columns
data['length'].plot(kind='hist')
<AxesSubplot:ylabel='Frequency'>
# Bag of Words (BoW) using CountVectoriser
f = feature_extraction.text.CountVectorizer(stop_words = 'english')
X = f.fit_transform(data["word_final"])
np.shape(X)
(2782, 2810)
X
<2782x2810 sparse matrix of type '<class 'numpy.int64'>' with 19326 stored elements in Compressed Sparse Row format>
# the below code we will run when we requie the Bag of words
#Transform the class_label to 1-0 (recode)
y=data["VSentiment"] #.map({'Positive':1,'Negative':0})
y.head()
#Create train and test samples
X_train, X_test, y_train, y_test = model_selection.train_test_split(X, y, test_size=0.30, random_state=42)
print([np.shape(X_train), np.shape(X_test)])
0 Negative 1 Negative 2 Positive 3 Negative 4 Negative Name: VSentiment, dtype: object
[(1947, 2810), (835, 2810)]
#Build a naive Bayesian model
from sklearn.naive_bayes import MultinomialNB
from sklearn.metrics import accuracy_score
mnb = MultinomialNB(alpha=0.2)
mnb.fit(X_train, y_train)
prediction = mnb.predict(X_test)
accuracy_score(y_test,prediction)
MultinomialNB(alpha=0.2)
0.8802395209580839
print(prediction)
['Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Negative' 'Negative' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Negative' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Negative' 'Positive' 'Negative' 'Negative' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Negative' 'Positive' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Negative' 'Negative' 'Negative' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Positive' 'Negative' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Negative' 'Negative' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Negative' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Negative' 'Negative' 'Positive' 'Negative' 'Negative' 'Positive' 'Negative' 'Negative' 'Negative' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Negative' 'Negative' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Negative' 'Negative' 'Positive' 'Positive' 'Positive' 'Negative' 'Negative' 'Positive' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Negative' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Negative' 'Negative' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Positive' 'Negative' 'Negative' 'Negative' 'Positive' 'Positive' 'Negative' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Negative' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Negative' 'Negative' 'Positive' 'Negative' 'Negative' 'Positive' 'Negative' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Negative' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Negative' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 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'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive']
test_df = pd.DataFrame(y_test)
test_df.head()
| VSentiment | |
|---|---|
| 1804 | Positive |
| 2164 | Positive |
| 1456 | Positive |
| 1480 | Positive |
| 2371 | Positive |
test_df['predictions'] = prediction
test_df.head(3)
| VSentiment | predictions | |
|---|---|---|
| 1804 | Positive | Positive |
| 2164 | Positive | Positive |
| 1456 | Positive | Positive |
test_df.head()
| VSentiment | predictions | |
|---|---|---|
| 1804 | Positive | Positive |
| 2164 | Positive | Positive |
| 1456 | Positive | Positive |
| 1480 | Positive | Positive |
| 2371 | Positive | Positive |
#Confusionn matrix for Naive Bayes
pd.crosstab(test_df.VSentiment, test_df.predictions)
| predictions | Negative | Positive |
|---|---|---|
| VSentiment | ||
| Negative | 128 | 24 |
| Positive | 76 | 607 |
from sklearn import metrics
from sklearn.metrics import classification_report
from sklearn.metrics import confusion_matrix
print(metrics.classification_report(y_test, prediction))
precision recall f1-score support
Negative 0.63 0.84 0.72 152
Positive 0.96 0.89 0.92 683
accuracy 0.88 835
macro avg 0.79 0.87 0.82 835
weighted avg 0.90 0.88 0.89 835
#Create Bag of Words (BOW) using tfidf
from sklearn.feature_extraction.text import TfidfVectorizer as tfidf
tfidf_vec = tfidf(stop_words = 'english')
x_tfidf = tfidf_vec.fit_transform(data["word_final"])
x_tfidf.shape
(2782, 2810)
x_tfidf
<2782x2810 sparse matrix of type '<class 'numpy.float64'>' with 19326 stored elements in Compressed Sparse Row format>
#Transform the class_label to 1-0 (recode)
y=data["VSentiment"] #.map({'spam':1,'ham':0})
y.head()
#Create train and test samples
X_train, X_test, y_train, y_test = model_selection.train_test_split(x_tfidf, y, test_size=0.30, random_state=42)
print([np.shape(X_train), np.shape(X_test)])
0 Negative 1 Negative 2 Positive 3 Negative 4 Negative Name: VSentiment, dtype: object
[(1947, 2810), (835, 2810)]
#Build a naive Bayesian model
from sklearn.naive_bayes import MultinomialNB
from sklearn.metrics import accuracy_score
mnb = MultinomialNB(alpha=0.2)
mnb.fit(X_train, y_train)
prediction = mnb.predict(X_test)
accuracy_score(y_test,prediction)
MultinomialNB(alpha=0.2)
0.8922155688622755
print(prediction)
['Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Negative' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 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'Positive' 'Negative' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive' 'Positive']
test_df = pd.DataFrame(y_test)
test_df.head()
| VSentiment | |
|---|---|
| 1804 | Positive |
| 2164 | Positive |
| 1456 | Positive |
| 1480 | Positive |
| 2371 | Positive |
test_df['predictions'] = prediction
test_df.head()
| VSentiment | predictions | |
|---|---|---|
| 1804 | Positive | Positive |
| 2164 | Positive | Positive |
| 1456 | Positive | Positive |
| 1480 | Positive | Positive |
| 2371 | Positive | Positive |
#Confusionn matrix for Naive Bayes
pd.crosstab(test_df.VSentiment, test_df.predictions)
| predictions | Negative | Positive |
|---|---|---|
| VSentiment | ||
| Negative | 103 | 49 |
| Positive | 41 | 642 |
from sklearn import metrics
from sklearn.metrics import classification_report
from sklearn.metrics import confusion_matrix
print(metrics.classification_report(y_test, prediction))
precision recall f1-score support
Negative 0.72 0.68 0.70 152
Positive 0.93 0.94 0.93 683
accuracy 0.89 835
macro avg 0.82 0.81 0.82 835
weighted avg 0.89 0.89 0.89 835